Accomplishments and Plans

of the

Climate and Global Dynamics Division

of the

National Center for Atmospheric Research

FY 1998 - 2003

Prepared for the

National Science Foundation

Peer Review

Submitted

May 1, 2001

TABLE OF CONTENTS

I. Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

II. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

A. Overview of NCAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

B. Overview of CGD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

III. Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Climate System Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

A. Achievements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

B. Plans. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Atmosphere and Land Research and Modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

A. Achievements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

B. Plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Ocean and Sea Ice Research and Modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

A. Achievements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

B. Plans. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Climate Diagnostics -- Observations and Model Studies. . . . . . . . . . . . . . . . . . . . . . 29

A. Achievements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

B. Plans. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Predictability of Weather and Short-Term Climate Variability . . . . . . . . . . . . . . . . . . . . . . 39

A. Achievements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

B. Plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

C. Activities in Response to the Previous Review. . . . . . . . . . . . . . . . . . . . . . . . . . 42

D. Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

IV. Linkages to Other Groups. . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
V. Education, Training, and Knowledge Transfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

A. Scholastic Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

B. Workshops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

C. Outreach Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

VI. Impact of Center Funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
VII. Financial Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
VIII. Appendices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

A. Publication List (1998-2001) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

B. Inventions, Patent Applications, and Patents . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

IX. Management Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

A. Management Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

B. CGD Staffing List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

C. Current and Pending Non-Base Support for Scientific Staff . . . . . . . . . . . . 95

D. Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
EXECUTIVE SUMMARY

This document reviews the achievements of the Climate and Global Dynamics (CGD) Division for the period fiscal years 1998-2000 and plans for fiscal years 2001-2003.

CGD’s research goal is to work towards a comprehensive understanding of the climate system components and the interactions among them, to represent this understanding in models of the components and the coupled climate system, and to provide a basis for prediction of weather and climate by using these models to investigate important scientific and societal questions. Research in CGD has two broad emphases: (1) understanding and predicting the earth system, and (2) climate variability. An integrating activity is the Community Climate System Model (CCSM) Project, which is funded by NSF Base Funds and the Climate Modeling, Analysis, and Prediction (CMAP) Program. Many CGD scientists, associate scientists and software engineers participate in this activity, together with staff members from other NCAR divisions, university scientists, and scientists from a variety of national laboratories.

Accomplishments in the past three years include the application of the Climate System Model (CSM) and the Parallel Climate Model (PCM), a similar model designed to work efficiently on parallel supercomputers, to a variety of important problems. A large number of simulations of the 20^th and 21^st Centuries have been run using a variety of scenarios generated by the IPCC or within NCAR. These data are stored either at NCAR or at Lawrence Livermore National Laboratory and are available to all interested scientists.

Improvements have been made to all CCSM component models. In order to make more effective use of massively parallel supercomputers, NCAR physics parameterizations have been put into the Parallel Ocean Program (POP), developed at Los Alamos National Laboratory (LANL), and thoroughly tested. The ocean model for CCSM-2 will run at somewhat higher resolution, 1 degree, and also have a new anisotropic viscosity parameterization. The sea ice model has been completely replaced with a model jointly developed at LANL, the University of Washington and NCAR. The new model has improved rheology and thermodynamics and performs well on parallel supercomputers. The land model has been improved, as well. A multi-institutional group has developed a Community Land Model, which is an improvement on the previously existing land models in use. A river runoff scheme developed at the University of Texas has been included.

The atmosphere model is being significantly changed, as well. An improved infrared radiation code, an improved cloud overlap parameterization and a cloud liquid water parameterization have been tested. Work has been done on two new dynamical cores, semi-Lagrange dynamics and a finite volume core developed by Lin and Rood. A new boundary layer scheme is being developed but not yet implemented. Other new parameterizations are being tested.

The earlier flux coupler has been modified to work on parallel supercomputers. A new, next-generation coupler is being designed in collaboration with software engineers at several DOE laboratories.

New components for CCSM-2 are being developed. Biogeochemistry components are being developed in the ocean and land models. The carbon cycle is the focus of the new work. The new land model will be generalized to include ecosystem dynamics. A Whole Atmosphere CCM (WACCM) is being developed that will allow study of the atmosphere from the surface to 140km and eventually to 500km. WACCM will be developed such that it will plug easily into the coupler and possibly be used as an atmosphere component in CCSM-2.

A major activity of CGD’s climate analysis and diagnostics has been the acquisition, evaluation and restructuring of data sets. A wide variety of empirical studies have been performed using these data, including studies of El Niño/Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the Tropical Biennial Oscillation (TBO) and temperature anomalies in the midlatitude oceans. Work has been done to reconcile the differences in the surface temperature record and the satellite record. A new data processing tool has been developed that is capable of dealing with data in a variety of formats, from observations and from CCSM. Training classes have been held, at NCAR and at universities, to teach people how to use this new tool.

Diagnostic studies have also been conducted on tropical Atlantic variability, atmospheric response to long-term trends in sea ice and midlatitude sea surface temperature anomalies, and mechanisms of midlatitude climate variability.

CGD scientists and collaborators have been active in developing adjoint models for a variety of purposes, including the development of an adjoint model containing moist physics, examination of predictability using singular vector decomposition and examination of the relationships between Lyapunov vectors, bred modes and singular vectors.

CGD scientists have also been involved in a variety of studies on predictability. These include a study of how predictability error growth affects the properties of an ensemble of predictions and a study of how the impact of using different methods for generating initial states in an ensemble affects the ensemble properties. Seasonal forecast skill was also investigated using ensembles of predictions generated by a variety of models.

CGD promotes education, training and knowledge transfer, through publishing results of research, convening workshops and seminars, appointing student staff, and a wide variety of public-information interviews, discussions, general articles and other mechanisms. CGD’s position in a center such as NCAR allows university collaborators, postdoctoral fellows, and students to have easy access to CGD’s models, data bases, and support personnel.

The division activities are managed by the director through a variety of mechanisms, including scientific advisory groups, interactions with NSF program directors, other NCAR division directors, and frequent interactions among the CGD staff.

II. INTRODUCTION

A. Overview of NCAR

The Climate and Global Dynamics (CGD) Division is one of nine divisions at the National Center for Atmospheric Research (NCAR). NCAR is managed by the University Corporation for Atmospheric Research (UCAR) and its 66 member universities.

NCAR’s principal missions are to conduct research into the atmospheric and related sciences; to provide the community with research tools and facilities including supercomputing, observing and sensing platforms, community models and data holdings, and other research instruments; to support and enhance education; and to facilitate the transfer of technology and information to the public and private sectors.

NCAR and UCAR work closely with the National Science Foundation to establish plans and priorities for NCAR’s programs that are appropriate in scope for a national center, are consistent with those of the research community, are responsive to national and international opportunities and initiatives, and represent important and challenging problems requiring teams of people working over an extended period.

University interactions are integral to NCAR’s research, facility development, community support, education, and information and technology dissemination. These interactions can be measured by research collaborations, both formal and informal, visitor programs and exchanges, community workshops and symposia, and short-term teaching and advising appointments.

NCAR’s programs benefit from broad community review and input into scientific initiatives, facility allocations, and field programs. Each NCAR division has an external advisory committee, drawn from experts in the field, to contribute advice on future plans and directions. Periodic comprehensive reviews such as this one provide community evaluation of the strength and health of the overall program.

NCAR’s research encompasses the broad spectrum of earth system science, including solar and solar-terrestrial processes; the chemistry of the atmosphere; interactions among the land surface, oceans, and the boundary layer between them; meteorological processes from the global to the microscale; the dynamics of the atmosphere and oceans; the earth’s climate; and the impacts of environmental processes and changes on society.

Facilities and tools available to the research community include computing resources; high-speed networks and data storage and retrieval systems; instrumented aircraft that can be deployed on large and small field programs; surface sounding and profiling systems; and models, software libraries, and data processing tools to help understand and simulate the earth system.

B. Overview of CGD

The mission of the Climate and Global Dynamics (CGD) Division is to understand Earth’s climate system and to develop the capability of predicting the evolution of the climate system to the degree possible. This requires a substantial effort in study of the observed data for the components of the system, the atmosphere, oceans, land surface, sea ice, and the biogeochemistry of these physical components. Because the observations are incomplete, to better understand the climate system we have developed models to simulate it. Using the models, we run experiments to analyze how the components interact and to compare the overall performance to observations, including known climate variabilities. Once a reasonable degree of faithfulness to observations is achieved, the models are used to perform experiments to determine how the climate system might evolve in response to anthropogenic changes in the environment. We also investigate the predictability of aspects of the climate system, and, when possible, develop models for use in prediction activities.

For several years, NCAR scientists, primarily in CGD, have been developing the Climate System Model (CSM). This model currently consists of models of the atmosphere, the oceans, the land surface, and sea-ice coupled together without the use of any artificial flux adjustments. As we work toward the second version of the coupled model, we believe that it is time to recognize the community of users and sponsors by changing the name of the model to the Community Climate System Model (CCSM). A Scientific Steering Committee (SSC) has been formed to lead the CCSM activity, working groups have been producing useful output, and the previously existing Climate Modeling, Analysis and Prediction (CMAP) Advisory Council has been reorganized as the CCSM Advisory Board (CAB). In addition to support from NSF, interest in the CCSM from other agencies, notably the Department of Energy (DOE) and NASA, has developed.

CGD's interaction with other divisions of NCAR is strong via our involvement in hosting the Geophysical Statistics Project (GSP) that collaborates on a wide variety of projects with most of the NCAR divisions. Other interdivisional interactions include the Geophysical Turbulence Program (GTP), the Whole Atmosphere Community Model (WACCM) with ACD and HAO, the U.S. Weather Research Program (USWRP) with MMM, the Clouds and Climate Program with MMM, aerosol research with ACD, biogeochemistry research with ACD, modernization of computer codes with SCD, Geosystems Databases with SCD, CCSM data processing with SCD, model for Ozone and Related chemical Tracers (MOZART) with ACD, and many individual collaborations between NCAR scientists.

The current CGD staff consists of 32 scientists (18 senior scientists), 30 associate scientists, 15 software engineers, 5 senior research associates, 4 systems administrators, 3 administrators, and 10 administrative staff. CGD currently has 10 long-term visitors, 10 postdoctoral students, and 3 student assistants. We are organized into six research sections, the Geophysical Statistics Project and a computer support group. The sections have been determined along related areas of climate research and there is a continual interaction among the sections.

The strength of our outreach to the university community is ensured through six affiliate scientists and a multitude of short-term visitors from all over the world. We communicate our results through scientific journal publications (106 refereed papers in FY 98, 112 in FY 99, and 107 in FY 00), scientific seminars, workshops, positions at universities, public presentations, and cataloging information on the World Wide Web (http://www.cgd.ucar.edu).

Some of the most significant accomplishment over the last three years are described in detail in Section III. Among those are:

· The June 1998 Journal of Climate issue was devoted to the NCAR CSM Version 1. Twenty articles described either the CSM component models or various aspects of the 300-year fully coupled CSM simulation run.

· The first CSM simulation of the 20th century climate was completed. The globally averaged temperature increased by about 0.6 K between the late 19th century and the 1990s, with most of the increase occurring since 1970, in agreement with observations.

· CSM simulations of the 20th and 21st century were carried out. For the 20th century, a control simulation, a transient simulation, a solar variability simulation including the reconstructed solar variation, and a greenhouse-gases only simulation were completed.

· The NCAR Paleoclimate Group improved the PaleoCSM (a low-resolution version of CSM) and completed multi-century, fully-coupled simulations for present-day, pre-industrial times, 1870 to present with volcanic episodic forcing, mid-Holocene, and Last Glacial Maximum.

· The U.S. National Assessment was released in November 2000 and presented an integrated view of climate impacts on all regions and many sectors of the U.S. The NCAR VEMAP team provided the historical and climate scenario information, as well as ecosystem model results, used in the National Assessment, translating, on a large scale, climate data and model results into forms designed for use by a broad stakeholder community.

· A distinct seasonal cycle in the structure and amplitude of interannual variability was quantified using NCEP/NCAR reanalyzes. CCM3 integrations with climatological SSTs, together with stochastically driven experiments with the linear barotropic vorticity equation, indicated the seasonal cycle of the mean circulation was largely responsible for this seasonal cycle of variability.

· Comprehensive diagnostic comparisons and evaluations were carried out with the NCEP/NCAR and ECMWF reanalyses of the vertically integrated atmospheric energy budgets.

· The simulated equatorial circulation of the CSM ocean component was dramatically improved through the incorporation of an asymmetric diffusion tensor allowing greatly reduced cross-stream diffusion.

· Idealized coupled model studies suggested that in the midlatitudes, atmospheric predictability was severely limited by the stochastic nature of its intrinsic low-frequency variability. The subsurface ocean exhibits significantly more predictability than the atmosphere.

· Climate Change experiments have been carried out using a varity of scenarios and the data have been analyzed and used in the most recent IPCC report.

· A system for forecasting aerosols was developed by staff members of CGD and ACD.

· Recent analyses of the global carbon cycle suggested a significant role for terrestrial uptake of CO₂ in the overall budget. Analyses of atmospheric CO₂ have persistently suggested that this terrestrial uptake is largest in the Northern Hemisphere, and spatial analyses suggest that the U.S. may play a disproportionate role.

III. RESEARCH

CLIMATE SYSTEM MODELING

In 1994, NCAR submitted a plan to develop a Climate System Model (CSM) to the National Science Foundation for review. CGD scientists proposed to develop a model within two years and make it available as a community model. At the time of the last NSF review of CGD, the Climate System Model was brand new and few results were available. Since then, significant progress has been made in many areas. Community-based management has been put into place. Working Groups have been established, which also include leadership from the community. Annual workshops have been instituted. A plan for development and application of the model over the next five years has been written. People have been hired to serve as liaison between NCAR and community participants. A significant amount of infrastructure has been established which has been extremely valuable in promoting community participation in the CSM project. For more details, please to refer to the web site, http://www.ccsm.ucar.edu/.

A. Achievements

300-Year Fully Coupled Control Simulation

Scientists from NCAR and the community have made significant progress in coupled climate modeling. The CSM was integrated for 300 years with atmospheric gas concentrations and solar irradiance fixed at present day values and held constant. After a brief period of adjustment, the simulation showed small surface climate drifts. This was the first experiment in which a coupled climate model was integrated for several centuries and produced a realistic climate without the use of flux adjustments. Over much of the globe, the annual mean simulated Sea Surface Temperatures (SSTs) had errors of less than 1 K. Other features of the simulated climate were similarly realistic. A description of the model and the features of this simulation were published in the June 1998 issue of Journal of Climate (20 articles, authors B. Boville, P. Gent, J. Kiehl, J. Hack, G. Bonan, D. Williamson, P. Rasch, J. Hurrell, B. Briegleb, F. Bryan, G. Danabasoglu, S. Doney, W. Holland, W. Large, J. McWilliams, G. Meehl, J. Arblaster, R. Saravanan, J. Weatherly and J. Chow (all of CGD), D. Bromwich (Ohio State University), M. Raphael (University of California, Los Angeles), and J. Maslanik (University of Colorado) .

Simulation of Transient CO₂ Increase

A coupled simulation in which the atmospheric carbon dioxide (CO₂) concentration increased by 1% per year was performed in collaboration with scientists from Japan's Central Research Institute of Electric Power Industry (CRIEPI). This simulation used initial conditions from the 300-year control run. The CO₂ concentration was held fixed at 355 ppmv for ten years, while atmosphere model data were output every six hours. CO₂ was then increased at 1% per year for 115 years, at which time the concentration had increased by a factor of slightly more than three. Output was again obtained every 6 hours for 10 years beginning at the time of CO₂ doubling. The 6-hour output was used by CRIEPI scientists as boundary and forcing data for regional model simulations. The globally averaged surface temperature increased by 1.25°K at the time

of CO₂ doubling and 2°K at the time of CO₂ tripling, consistent with a 2°K equilibrium temperature increase simulated by the Community Climate Model version 3 (CCM3) coupled to a slab ocean.

Simulation of the 20th Century Climate

Several CSM simulations of the 20th century climate have been performed. A new spin-up and a 270-year control simulation of the coupled system for 1870 conditions were performed (Boville et al., 2001). Four transient forcing simulations were then performed using reconstructions of atmospheric concentrations of sulfate aerosol, CO₂, ozone (O₃), methane (CH₄), nitrous oxide (N₂O), and chlorofluorocarbons CFC11 and CFC12. The latter four gases were advected in the CSM. CFC11 concentrations were scaled to account for the effects of other halocarbons. The globally averaged temperature increased by about 0.6°K between the late 19th century and the 1990s, with most of the increase occurring since 1970, in agreement with observations. The CSM simulations showed levels of variability that compare well to the observed record prior to 1920, but it did not capture the observed maximum in the 1940s, which is believed possibly to have been caused, in part, by variations in solar irradiance. A single simulation adding a reconstruction of the solar irradiance variations since 1870 was inconclusive, due to the model’s internal variability.

The effect of the simulated global temperature increase after 1970 can be clearly seen in the evaporation and precipitation, which increased after 1970. The effect on the runoff rates was less clear. Although global runoff increased at the end of the simulation, it was not outside the range of variability found earlier in the simulation, before the temperature and precipitation increased significantly. There was some evidence of increasing snow accumulation in Antarctica and increased runoff in a few basins, but other basins showed no significant change.

21st Century Climate Scenarios

Realistic initial conditions for five simulations of the 21^st century, beginning at 1980, were obtained from one of the 20^th century simulations described above. Since the geographic distribution of anthropogenic sulfur dioxide emissions are expected to change with time, the sulfate aerosol model was solved interactively in the 21^st century simulations. The concentrations of the same greenhouse gases as in the 20^th century simulations and the distribution of sulfur dioxide emissions were specified as a function of time. Time series were constructed for a “business as usual” scenario and for a plausible “policy-limited” emissions scenario, and simulations were performed using them. The “business as usual” scenario produced an increase of 1.7° K in the global average surface temperature in the 21^st century. The global average surface temperature increased by 1.3 °K in the “policy limited” scenario, with the rate of increase slowing after 2050. When the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) became available, additional simulations were performed for the A1, A2 and B2 scenarios. The scenarios produced temperature increases consistent with those from the earlier scenarios. The A2 scenario corresponds quite closely with the “business as usual” scenario and gives similar results. The B2 scenario corresponds reasonably with the “policy-limited” scenario and gives similar results. The forcing in A1 is larger than in the “business as usual” scenario and the temperature increase was 2.2° K over the 21^st century.

The North Atlantic Ocean thermohaline circulation was studied in three experiments using the fully coupled CSM. They are the control integration for 1870 conditions and particular emission scenarios for the 20^th and 21^st centuries. Gent (2001) showed that the strength of the North Atlantic thermohaline circulation does not change significantly over the 21st century. This result contrasts with several recent studies done at other climate centers that have projected a significant reduction over the 21^st century. The reason for the difference is that the Northwest Atlantic becomes warmer and salinity increases in the CSM. These changes combine to make little change to the surface ocean density in this region, and hence to the rate of deep-water formation.

Five year running mean global averaged surface air (2 m reference height) temperature anomalies for the CSM 20^th Century simulations, two CSM 21^st century scenarios and two PCM 21^st century scenarios, with respect to the CSM constant-1870 control simulation (black). Also shown is the observed global temperature record since 1860.

DOE-Sponsored Climate Change Research

The Department of Energy’s (DOE) comprehensive climate modeling research program includes climate model diagnosis and prediction of climate change from increasing greenhouse gas concentrations and other forcings of the climate system. NCAR’s part of this research has been accomplished through collaborations among NCAR, Naval Postgraduate School (NPS), Los Alamos National Laboratory (LANL), Oak Ridge National Laboratory (ORNL), Argonne National Laboratory, U.S. Army Cold Regions Research and Engineering Laboratory (CRREL), Lawrence Livermore National Laboratory's Program for Climate Model Diagnosis and Intercomparison (PCMDI) and several universities. This project has emphasized decade-to-century climate change projections. With the above collaborators the Parallel Climate Model (PCM) was developed. The CSM was originally developed to run on vector supercomputers. PCM is capable of efficiently executing on the DOE parallel supercomputers. CSM and PCM share atmosphere and land model components. The CSM ocean model was based on the Modular Ocean Model, version 1, which does not parallelize well. The PCM ocean model uses the Parallel Ocean Program (POP), developed at LANL specifically for parallel supercomputers. Ocean model physics was different in the two models. The sea ice models were also different, with the model used in PCM performing better on parallel machines. The DOE program is tightly linked to DOE's component of the High Performance Computing and Communications Program through the High Performance Computing Research Centers at Los Alamos and Oak Ridge National Laboratories.

Control, Ensemble Experiments: 1% Per Year CO_2, Historical and Future Climate

Results from a 300-year present-day PCM coupled climate control simulation by W. Washington, Weatherly (CRREL), Meehl, A. Semtner (NPS), T. Bettge, A. Craig, G. Strand, J. Arblaster, V. Wayland, R. James (SCD), and Y. Zhang (NPS) showed that the PCM gave a stable simulation of surface climate with approximately the observed interannual and decadal variability.  Five transient 1% per year CO₂ increase experiments have been performed that showed a global warming of about 1.3°C for a 10-year average at the doubling point of CO₂. One of these was run an additional 130 years with CO₂ amount held constant at double the present value. Another of the experiments was allowed to go to the quadrupling point, where the global average warming was 2.9°C. This experiment was then run for an additional 130 years with CO₂ held fixed at four times the present value. There was a gradual global surface warming beyond the doubling and quadrupling points. Examination of El Niño events in the doubled and quadrupled CO₂ environments showed little change in amplitude or frequency of ENSO in the future (Washington et al., 2000).

Ten historical PCM ensemble simulations from 1870 to 2000 and five each "business as usual" and “policy intervention” simulations from 2000 to 2100 have been conducted. The simulations make use of the same forcing as the CSM (Dai et al., 2001).   Four additional simulations with the added effect of solar forcing on the climate system have been conducted for the period 1870-2000. Single runs have been made with the new IPCC SRES marker scenarios A2 and B2.

A major question that has arisen in climate change simulations is why models respond differently to the same forcing. To address this question, Meehl, Boville, Kiehl, W. Collins (CGD), T. Wigley (CGD) and Arblaster analyzed the 1% per year CO₂ increase experiment performed with the CSM in comparison to a similar experiment with the earlier DOE global coupled model. The role of amplifying processes in the tropical Pacific related to cloud feedbacks, and in high latitudes involving sea ice feedbacks, was compared to address the question of how these processes contribute to different global climate responses in the two models (Meehl et al., 2000c). The El Niño-like response in the tropical Pacific was estimated to enhance the globally averaged temperature response about 10%, while different ice-albedo feedback processes can make more than 15% difference in the globally averaged temperature response.

The simulation of near-observed El Niño amplitude in the PCM compared to earlier low El Niño amplitude in the first version of CSM (Meehl and Arblaster, 1998) prompted Meehl, in collaboration with Gent, Arblaster, B. Otto-Bliesner, E. Brady and Craig, all of CGD, to compare the behavior of El Niño in ten different runs of CSM and PCM. There are similar systematic errors in the pattern of El Niño variability (extending too far west into the warm pool) and eastern Pacific seasonal cycles (SSTs too semiannual, double Intertropical Convergence Zone (ITCZ) in all model runs. However, the lower the value of background vertical diffusivity, the sharper the thermocline and the higher the amplitude of El Niño variability (Meehl et al., 2001a).

Paleoclimate

The development and application of the PaleoCSM has been carried out by Otto-Bliesner, Brady, and C. Shields (CGD). The PaleoCSM is a version of the CSM that uses a T31 resolution for the atmosphere and land models and the x3' grid for the ocean and sea ice models. The PaleoCSM allows specification of the solar constant, atmospheric trace gases, Milankovitch orbital variations of the solar insolation, continental configuration and ocean bathymetry, vegetation and soil characteristics. This version of the CSM is being widely used for studying past climates both within NCAR and at numerous universities. The Paleoclimate Group is an active member of the NSF-sponsored Partnership for Modeling Earth System History (PMESH).

A significant accomplishment over the last five years is the realistic depiction of the El Niño/Southern Oscillation (ENSO) in the PaleoCSM, thus providing a tool for the first time to enable studies of changes of El Niño events in past climates (Otto-Bliesner and Brady, 2001). This improvement was accomplished in collaboration with ocean modelers Gent and Large. This new version of the PaleoCSM significantly improves the amplitude and spatial and temporal patterns of tropical Pacific variability. The evolution of SST and subsurface temperature anomalies is in excellent agreement with observed events. The majority of warm events evolve as a standing mode with weak SST anomalies occurring in the northern spring in the eastern tropical Pacific and maximum anomalies covering the eastern tropical Pacific Ocean to the dateline by the following northern winter. The "delayed oscillator" and Wyrtki's "buildup" hypothesis are consistent with aspects of the CSM simulation.

The PaleoCSM has been used to explore the role of Milankovitch orbital variations of incoming solar insolation on the coupled climate system. Particular attention has focused on the nonlinear effects of the seasonal and latitudinally varying changes of incoming solar insolation on ENSO variability in the tropics and sea ice extent/warming in the Arctic. A series of 100-year simulations has been completed for the Holocene (3.5 ka, 6 ka, 8.5 ka, and 11 ka) and for the last Interglacial (125 ka). Although annual mean insolation in the Arctic is unchanged compared to present, the enhanced summer-fall insolation at these latitudes results in later sea ice formation in the fall and warmer annual surface temperatures for the circum-Arctic land areas. Enhanced summer-fall insolation in the tropics compared to present modifies the seasonal cycle of eastern tropical Pacific SSTs, resulting in weaker ENSO. These results correlate well with proxy records of Holocene ENSO.

Additional Quaternary simulations have been completed in collaboration with university researchers. A coupled simulation for the Last Glacial Maximum (21 ka) completed with S.‑I. Shin and Z. Liu (University of Wisconsin) gives cooling of 2-20°C as a result of the reduced levels of greenhouse gases and the massive Northern Hemisphere continental ice sheets. Sensitivity CCM3 simulations completed with L. Smith and G. Miller (University of Colorado) demonstrate the importance of accurately delimiting sea ice margins in the past, both for the marine environment and for the downstream terrestrial realm. The simulations confirm the importance of developing multiple proxies to provide a full sea ice reconstruction.

Another accomplishment has been the completion of the first long, fully coupled simulation for the warm Cretaceous climate period of 80 million years ago. During this period, the continental configuration and ocean bathymetry were significantly different from the present, atmospheric CO₂ may have been as high as 6 times pre-industrial levels, and proxy evidence suggests deep ocean temperatures 8-12°C warmer than present. Enhanced CO₂ levels result in significantly warmer SSTs, tropical SSTs ~4°C warmer and polar SSTs 6-14°C warmer than present, and no perennial sea ice. The sea surface salinities simulated for the Cretaceous period are also significantly different than those simulated for present, with the North Pacific basin experiencing higher salinities and the narrow North Atlantic basin quite fresh. Large overturning cells occur in both hemispheres with sinking at ~60 latitude, rather than at subtropical latitudes as conjectured from conceptual models. Simulated deep-water ocean temperatures are in agreement with proxy records.

The Climate of the 17th-18th-19th-20th Centuries (CSENT) Project has completed benchmark simulations for the late 19th and 20th centuries that include volcanic forcing in addition to solar, aerosol, and trace gas forcings. This is a collaborative effort of C. Ammann (University of Massachusetts), Otto-Bliesner, and Kiehl. A significant impact of the volcanoes was found for a number of tropical eruptions: Krakatau 1883, Santa Maria 1902, Agung 1963, El Chichon 1982, and Pinatubo 1991. High latitude eruptions like Katmai-Novarupta in 1912 only perturbed the respective high latitudes for a few of months. For the big tropical eruptions, the injection causes substantial warming of the stratosphere by several degrees Celsius, and with a several month delay, a significant cooling of several tenths to over 1°C around 400 hPa, and several tenths of a degree C at the surface. The coupled CSM experiment confirms the significant short-term cooling, as well as a longer-term recovery, from a set of eruptions. The simulation with all the natural and anthropogenic forcing confirms the important effects of both solar variability and volcanic episodes on the global temperature variations in the early part of the 20th century, with trace gas forcing becoming dominant since 1970.

B. Plans

In recognition of the increased interagency collaboration on this project, the name of the model has been changed to the Community Climate System Model (CCSM). A new version of the CCSM, CCSM-2, is in development. NCAR scientists and our partners in DOE and NASA have agreed to collaborate on climate model development with emphasis on redesigning the climate model components and the method of coupling components for the parallel supercomputers. NCAR scientists and software engineers are involved in DOE’s CCSM Avant Garde project, which is designed to re-program the CCSM components so that they perform more efficiently on parallel computer systems. NCAR software engineers are taking the lead in developing the next generation flux coupler. We expect that the new model will produce improved simulations of the mean climate and climate variability and will reduce deep-ocean drifts. We will perform an extended, multicentury simulation of the recent past climate. The data will be made available to the CCSM community.

From the beginning of this project, we have expected that new components of the CCSM would be developed. One such capability concerns biogeochemistry. The CCSM Biogeochemistry Working Group, a multi-institutional group of scientists working on CCSM, has begun planning the “Flying Leap Experiment”, in which fossil fuel carbon emissions will be specified, carbon will be actively advected through the system, dissolved in and released from the ocean, and taken up by the land surface. Atmospheric concentrations of carbon will be determined as a residual of these interactive processes. It seems likely that the first experiment will require refinement and further model development and that subsequent experiments will be necessary to answer detailed questions about the carbon budget. This work will continue over the next five years.

We expect that the next five-year period will be characterized by increased model complexity and capability, with the model being used for more experiments that have not yet been attempted. These could include studies of recent climate change due to change in land surface properties, or climate change and its consequences for ecosystem succession. Which experiments will be performed depends on the rate of model development and validation and the availability of computer time. The CCSM Scientific Steering Committee (SSC) will continually evaluate the status of the model and its readiness for possible experiments and determine how to use the computer resources that are available.

Climate Change

CCSM-2, which is expected to be available in 2001, will be used to contribute to the next National Climate Assessment and to the next IPCC report, due in 2005. Global change simulations will be an ongoing activity using improved and higher resolution models. Part of the activities of the CCSM Climate Change and Assessment Working Group will be to conduct climate change simulations with CCSM-2 using the most recent IPCC SRES scenarios for subsequent analysis, intercomparison, and assessment activities. In support of the DOE Climate Change Prediction Program (CCPP) Demonstration Project, NCAR scientists will conduct climate change simulations with CCSM-2 using observed ocean data as initial conditions and making climate change projections to the year 2100. This project will provide data for the regional climate modeling and climate impacts communities.

The NCAR coupled climate models (CSM and PCM) have produced an extensive and unique archive of ensemble climate change experiments. Numerous studies can be performed, and these simulations will continue to be analyzed. Research topics include changes of the North Atlantic Oscillation and ENSO. Additional studies that are planned include analysis of changes in diurnal temperature range in the 20^th and 21^st centuries, examination of the mechanisms associated with those changes and additional studies of changes in weather and climate extremes related to thresholds of extreme events.

Paleoclimate

Future research activities by the CCSM Paleoclimate Working Group will include exploring the transient nature of the climate response with 1) simulations of abrupt change over the last glacial-interglacial cycle, particularly the 8.2 ka event and the Younger Dryas, and 2) an evaluation of the importance of solar and volcanic forcing on the climate since 1500. The last interglacial period (125 ka), a very warm period, will be extensively studied in conjunction with PARCS (Paleoenvironmental Arctic Sciences) scientists. In addition, the paleoclimate group will be working closely with the CCSM Land Working Group and R. Gallimore and J. Kutzbach (University of Wisconsin) on Quaternary climate simulations, which also include interactive vegetation dynamics.

For a more detailed discussion of the achievements and plans for the CCSM, see the Community Climate System Model Plan 2000-2005, available at http://www.ccsm.ucar.edu/management/plan2000/index.html.

ATMOSPHERE AND LAND RESEARCH AND MODELING

Scientists in CGD develop, maintain and apply atmosphere and land models for climate research. Over the past three years CGD scientists have continued to develop parameterizations for the Community Climate Model (CCM) and have also played an integral role in the CSM Atmosphere Model Working Group. Research includes development of cloud parameterizations, aerosol models, radiation models, and numerical methods. Research has also been carried out in the areas of cloud-aerosol-climate interactions, land surface-biogeochemical research and middle atmosphere studies.

A. Achievements

Aerosol Research

Extensive research in global aerosol modeling has taken place over the past three years. This program includes modeling aerosol concentrations, the optical properties of the aerosols, and their climate effects. A unique component of the program is the development of an aerosol data assimilation program for use in field programs and creation of global aerosol datasets.

Emission of sulfur dioxide into Earth's atmosphere leads to the production of sulfate aerosols, which reflect short wave radiation back to space and thus cool the climate system. The aerosols also indirectly affect cloud properties by changing the number distribution of cloud drops. Kiehl, Rasch, and M. Barth (Atmospheric Chemistry Division, ACD) used a version of the NCAR CCM3, which includes a sulfur chemistry model, to assess the direct and indirect radiative forcing of sulfate aerosols. This study found a large range of uncertainty in the magnitude and spatial distribution of direct forcing. It also found that the inclusion of a background aerosol as a source of cloud nucleation reduced the magnitude of the indirect effect by a factor of two.

Hack, Kiehl, and V. Ramanathan (Scripps Institution of Oceanography) used data from the Indian Ocean Experiment (INDOEX) to prescribe the distribution of the aerosols and their optical properties for use in the CCM3. A series of simulations with the CCM3 with prescribed SSTs and predicted SSTs from a slab ocean model were carried out. These simulations indicate that the absorbing aerosols produce heating aloft associated with an elevated aerosol layer and cooling of the land and ocean surface. The atmospheric heating results in establishing a diabatic gradient that leads to a northward shift in the ITCZ precipitation in the Indian Ocean. The effect of the aerosol on the diurnal cycle of clouds is to decrease shallow convective activity at local noon.

Collins and Rasch constructed the first aerosol modeling system combining a chemical transport model and an assimilation of aerosol properties obtained from remote sensing. The assimilation scheme helps improve the fidelity of the model on short space and time scales, and it can be used to improve the representation of aerosol sources and evolution in the model. This system was used to provide aerosol forecasts during INDOEX to help guide deployment of the experimental aircraft. After completion of INDOEX, Collins used the system to provide a large-scale analysis of aerosols in the Indian Ocean basin. These results from the assimilation were used to compute the radiative forcing of aerosols over the Indian Ocean and surrounding continental areas.

Atmospheric Radiation Research

CGD research in atmospheric radiation has focused on studying the existence of enhanced shortwave absorption, development of a generalized cloud overlap scheme and development of a new parameterization of the longwave treatment of water vapor.

The debate on how the solar radiation absorbed by the planet is partitioned between the atmosphere and surface has been renewed by several recent observational studies. The preponderance of experimental evidence suggests that there is more absorption in cloudy regions than predicted by models. One of the traditional indices of this enhanced cloud absorption is the difference in spectral cloud albedos from models and observations. Collins used a nine-year global record of spectral albedos from the Nimbus-7 satellite to compute the ratio of near-infrared to visible cloud albedo over oceans. The Nimbus-7 data were compared to the NCAR CCM and to the NCAR Column Radiation Model (CRM) applied to satellite cloud retrievals. The results show that there is a persistent anomaly in the spectral albedo ratio for cloudy regions, while there is no evidence of an anomaly for relatively cloud-free regions.

Inclusion of this absorption in a general way into the CCSM indicates that the compensating errors in insolation and latent heat flux are eliminated in the tropical Pacific. The individual terms in the simulated energy budgets at the surface and top of atmosphere (TOA) are in excellent agreement with observations; the biases in simulated SST are reduced to less than 1°K, and transient artifacts in the coupled integration are reduced by approximately 50%. This is the first study examining the effects of enhanced absorption on coupled climate simulations, and it suggests that resolution of the existence and physical mechanisms of enhanced absorption are important for modeling climate.

Collins has also completed work on modernizing the treatment of longwave (thermal) atmospheric radiation in collaboration with members of ACD.

Clouds and Climate Research

CGD cloud development activities focused on the role of diabatic processes in maintaining the atmospheric general circulation. This included the interaction and relative roles of boundary layer, moist convection, and radiation processes in defining the total diabatic forcing of the atmosphere. Hack and Kiehl developed a new cloud optical property parameterization, which includes new techniques for diagnosing cloud liquid water content and cloud particle effective radius, and diagnostic analyses of climate simulations including the hydrological cycle, the simulated energy budget, and a variety of dynamical topics. Other work has included the analysis of the implied meridional ocean energy transport in the global model. Hack showed that the correct representation of the TOA energy budget is a necessary, but not sufficient, condition for obtaining the observed meridional structure of the ocean energy transport. Rasch studied the sensitivity of convection to thermodynamic triggers of convection and how it interacts with large scale meteorological flows (like the Madden-Julian Oscillation).

A parameterization for stratiform cloud condensate and precipitation was developed with J. Kristjansson (University of Oslo). This parameterization interacts with the other components of the hydrologic cycle and radiative transfer components of the CCM. In addition, the parameterization of cloud water is also used in the representation of the production and loss of atmosphere aerosols discussed below, via aqueous oxidation of sulfur dioxide and scavenging of hydrophilic aerosols.

Land Surface Science

Bonan’s Land Surface Model (LSM) is a one-dimensional model of energy, momentum, and water exchange between land and atmosphere. Initial applications of the model emphasized key ecological (e.g., changing land cover) and hydrological (e.g., lakes, soil water) influences on climate. Bonan, in collaboration with the CCSM Land and Biogeochemistry Working Groups, expanded this model from a traditional land model emphasizing biogeophysics to include three other areas of land surface processes: biogeochemistry, catchments hydrology and river flow, and vegetation dynamics.

Significant improvements have been made in the parameterization of soil temperature and water, snow processes, runoff generation, and surface energy exchange. A grid cell-based river routing scheme has also been added to the model. The improved model takes the runoff generated by the column biogeophysics and routes the water downstream into the oceans. Many biogeochemical processes are controlled by surface biogeophysics. The emission of volatile organic compounds (VOCs) is controlled by light, leaf area, temperature, and plant type. These variables are already in the model, allowing for implementation of VOC emissions. Similarly, entrainment of dust in the atmosphere is controlled by turbulence, soil moisture, soil texture, and land cover, also already present in the model. As a result, a dust emission scheme is being added to examine the effect of dust on climate. Finally, substantial progress is being made to include a dynamic global vegetation model into the CCSM land model to provide an integrated terrestrial model.

Intercomparison of Terrestrial Biogeochemical Models – VEMAP Phase 2

Integral to incorporation of land carbon processes into climate system models is the evaluation of extant state-of-the-art terrestrial biogeochemical models. The Vegetation-Ecosystem Modeling and Analysis Project (VEMAP) is a large, collaborative, multiagency program to simulate and understand ecosystem dynamics for the continental U.S. The international collaboration includes scientists from NCAR (D. Schimel and T. Kittel, CGD), University of Montana, Oregon State University, Colorado State University, The Ecosystems Center of the Woods Hole Marine Biological Laboratory, University of Alaska-Fairbanks, University of Virginia, Oak Ridge National Laboratory (ORNL), University of Sheffield (UK), University of Lund (Sweden), and Max Planck Institute for Biogeochemistry (Germany). The project has carried out its second phase of experiments comparing time-dependent ecological responses of biogeochemical models and dynamic global vegetation models to historical and projected transient climate and CO₂ forcings across the U.S.

The most significant accomplishment of VEMAP Phase 2 to date was to estimate recent historical terrestrial carbon sink/source dynamics in the U.S. (Schimel et al., 2000). The models suggest a sink due to CO₂ fertilization, climate, and agriculture in the late 20th century. For the period 1980-1993, the models simulated a land carbon sink from CO₂ fertilization and climate effects of 0.08 Gt C per year (±25%). This is a much lower value than an atmospheric-based calculation by Fan et al. Even though the VEMAP estimate does not include all carbon sink processes, it challenges the atmospheric estimate.

Another VEMAP Phase 2 accomplishment was the development of common model input data sets (climate, vegetation, soil) that permitted model intercomparison experiments. The VEMAP Phase 2 historical and future climates dataset was developed in a joint effort between CGD (Schimel, Kittel, N. Rosenbloom) and Geophysical Statistics Project scientists (D. Nychka, J. Royal), in collaboration with researchers at the Oregon Climate Service, University of Montana, and University of East Anglia, UK (Climate Impacts Group/LINK). This data set is a gridded (0.5° lat./lon.), temporally-complete (1895-2100), multiple timestep, and multivariate (7 variables) database. To date, distribution of the data set through the NCAR web site has been made to over 35 U.S. universities and institutions, 8 national labs and agencies, 4 private companies and organizations, and 6 foreign sites and through the ORNL Distributed Active Archive Center (DAAC) to 37 U.S. universities, 17 agencies and organizations, and 36 foreign sites.

Whole Atmosphere CCM

The Middle Atmosphere Community Climate Model (MACCM) is an upward extension (model top is at about 85 km) of the NCAR CCM and has been used to investigate the nature of the Brewer-Dobson circulation in the middle atmosphere under different conditions of parameterized gravity waves. The role of gravity waves in the middle atmosphere was examined in the context of changes to the circulation and to the dissipation of planetary waves that, cooperatively with radiation, determine the behavior of the polar vortex and the distribution of stratospheric constituents. Age of air calculations have been used to quantify the contemporaneous effects of wave mixing and advection, showing that MACCM reproduced the age estimated from observations. In collaboration with scientists in ACD, CGD researchers used winds and thermal fields generated in those simulations in off-line chemical/transport calculations of the middle atmosphere.

The Whole Atmosphere Community Climate Model (WACCM) is an outgrowth of MACCM. WACCM is a cooperative effort among CGD, ACD and the High Altitude Observatory (HAO). The goal is to obtain a global circulation model from the ground to the lower thermosphere to study the climate of the middle and upper atmosphere. Appropriate parameterizations for the upper atmosphere have been included in WACCM. These include non-LTE longwave cooling; solar heating below 200 nm; ion drag; molecular viscosity with constant flux upper boundary condition; and vertical extension of the gravity wave parameterization, including wave dissipation by molecular viscosity, gravity waves transport, and heating.

A preliminary version of WACCM with the model top at about 140 km has been successfully run for 20 years. Winds generated by this simulation are currently being used in off-line chemical/transport calculations with the Model for Ozone and Related Chemical Tracers (MOZART) version 3 chemical code. Comparison to other models such as the Thermosphere Ionosphere Mesosphere Electrodynamics General Circulation Model (TIME/GCM) and to observations, i.e., Upper Atmosphere Research Satellite (UARS), suggest that the WACCM model is performing well.

Chemistry-Climate Research

Rasch has developed an off-line Model of Atmospheric Transport and Chemistry (MATCH) for representing trace constituent evolution in the atmosphere. This model is used at a number of institutions around the world. It has been used for forecasting the realistic evolution of trace species distributions in real time as well as more abstract theoretical studies, in applications ranging from aerosol transport near the surface to theoretical "age of air'' applications relevant in the middle atmosphere. Rasch has also developed new numerical methods, which are useful for the transport of trace species in the atmosphere. These methods are monotonic, conservative, and accurate for transport in global models.

Using a combination of observations and chemical modeling, Kiehl, with R. Portmann and S. Solomon (both NOAA Aeronomy Laboratory) developed a data set for the three dimensional distribution of tropospheric and stratospheric ozone. These ozone data were used in a version of the CCM3 to calculate the radiative forcing over the past century due to changes in ozone. These results investigated the importance of defining preindustrial ozone levels for the forcing calculations. The calculations indicate that positive radiative forcing from increased tropospheric ozone cancels up to 50% of the negative forcing from the direct effect of sulfate aerosols.

CCM Single Column Model

Hack developed a single column model (SCM) of the CCM3. Scientific investigations using this tool, in boundary-layer and convection parameterizations, have exposed strong simulation sensitivities to the details of how the parameterized physics is forced with observations. Unconstrained ensemble solutions can exhibit multiple solution states during various phases of the simulation where these solutions oscillate about the ensemble mean solution. This multiple attractor behavior is characteristic of highly nonlinear systems and illustrates the need for the statistical characterization of single column model solutions. The most intriguing property of these solutions is the collapse of multiple states back to a single state, suggesting the presence of a strong restoring force in the system, which is believed to be associated with the SCM equilibrium state.

Numerical Methods, Next Generation Models

D. Williamson and J. Olson developed three- and two-time-level semi-Lagrangian approximations for global atmospheric models and studied their application to climate simulation with versions of the CCM. It was shown that a minimum of 1.5 km vertical resolution is required around the tropopause. It was also shown that the semi-Lagrangian approximations have much better vertical noise characteristics than the Eulerian approximations. Reduced grid approximations were developed for both Eulerian and semi-Lagrangian versions of CCM. The actual grid definition is based on properties of the associated Legendre functions. It was demonstrated that an adiabatic Eulerian spectral transform model is in fact accurate to the degree expected from the grid definition. It was also shown that the climates produced by the models and run on full and reduced grids are all very similar, with no indication of pathological errors. The net efficiency gain from the combination of semi-Lagrangian approximations and reduced grid exceeds a factor of ten at climate application resolutions.

A new design for the CCM was implemented in which the parameterization suite can be coupled to the dynamics in either a time-split or process-split manner. Adopting different coupling strategies is only warranted if the difference in errors is relatively small so that the coupling strategies do not dominate the simulation. Collaborations were established with staff from NASA/Data Assimilation Office (DAO) and DOE, ORNL, Argonne National Laboratory (ANL), LLNL, and Lawrence Berkeley National Laboratory (LBNL) to convert the CCM code to a form which easily allows the exchange of dynamical cores on a wide variety of computers.

Studies with resolutions from T42 to T170 with CCM2 and CCM3 show that critical aspects of the simulated climate do not converge up to T170 and that even the large scales, greater than T42 do not converge. Additional experiments in which the grid and scale of the physical parameterizations are held fixed while the horizontal resolution of the dynamical core is increased show that the nonconvergence was due to the nonlinear interactions of smaller scales feeding back on the larger scales.

CGD scientists are also developing expertise needed for future-generation global atmospheric models. It will soon be possible to analyze and forecast weather and climate with global models having a horizontal grid size of 10 km or less. For such very-high-resolution global atmospheric models, it will be important to consider nonhydrostatic effects that are traditionally neglected in global hydrostatic prediction models.

Kasahara (CGD) and J. Qian, International Research Institute, (Lamont Doherty Earth Observatory-IRI, LDEO) developed the basic tools to examine the roles of large-scale acoustic motions together with those of gravity waves and planetary-scale motions. The mechanism of hydrostatic adjustment can be investigated along with global geostrophic adjustment.

The next generation global model will additionally be required to execute efficiently in a parallel architecture environment and be capable of locally refining its resolution. To address these requirements, Tribbia, with F. Baer (University of Maryland) and M. Taylor (LANL) has explored the efficacy of the spectral element method on the sphere. A spectral element dynamical core has been developed which is competitive with current spectral models. Because of the modular flexibility of this model, it is worthy of serious consideration for general parallel architectures. It has the added benefit of being easily adaptable for studies that require local mesh refinement, like regional climate simulation, in a manner that will retain spectral accuracy of the numerics.

B. PLANS

CGD scientists will develop and improve numerous aspects of the atmospheric and land models. Particular emphasis for climate applications will be placed on generalizing the model to include aerosols, chemistry, and biogeochemistry. Emphases for climate and weather modeling include nonhydrostatic models and modern numerical schemes.

Kiehl and Ramanathan will run simulations with a global distribution of absorbing aerosol to investigate the relative importance of TOA forcing versus surface and atmosphere forcing. An idealized distribution of heating will be applied to the CCM3, which will imply no change in the TOA radiative forcing but significant forcing at the surface and atmosphere. Equilibrium simulations will be carried out in CCM3. Collins, Kiehl, and Rasch will incorporate the comprehensive aerosol model into a future version of the CCSM Atmosphere Model to study the effects of aerosols on climate forcing and response to various aerosol compositions. Rasch will develop better microphysical representations of ice and mixed phase clouds and the interaction between aerosols and cloud-drop formation.

Collins and Rasch will also provide aerosol forecasts for the Aerosol Characterization Experiment-Asia (ACE-Asia), and an aerosol analysis for ACE-Asia will be developed by assimilating in situ and remotely-sensed observations. The aerosol system will be extended to include data from the current generation of NASA satellites and upcoming NASA space-based lidars. The lidar data will be used to adjust the vertical location of the aerosols in our aerosol models. Since the lifetime of aerosols grows very rapidly with altitude, this new assimilation system should produce much more accurate simulations of long-range transport of these particles.

Hack will continue work in the area of parameterization of diabatic processes in global climate models, such as moist convection. Parameterization of convection will be closely coordinated with resolution studies conducted by investigators working on numerical methods, and with efforts to produce tighter coupling between physical parameterizations.

Bonan will focus on continued development of the biogeophysical parameterizations in the model and extension of the biogeochemical and vegetation dynamics capabilities of the land model. Areas of research include albedo and radiative transfer, canopy physiology, snow processes, runoff generation, and utilization of satellite data products. The remote sensing community is developing new land cover and surface biogeophysical data products. These products can be developed in tandem with the model.

Bonan will work to include a full carbon cycle with vegetation dynamics in the land model. The prototype coupling of CLM with a dynamic global vegetation model will provide a starting point for further development. In conjunction with the CCSM Biogeochemistry Working Group, ecological processes such as respiration, allocation, litterfall, disturbance, and decomposition will be refined to take advantage of recent ecological insights.

In VEMAP Phase 2, ecological model experiments for the next century were driven only by climate and CO₂ scenarios. In VEMAP Phase 3, land cover change and disturbance dynamics will be addressed directly and in concert with climate and CO₂ change. Specific land use and disturbance factors to be included are agricultural practices, farm abandonment, grazing practices leading to woody encroachment, fire suppression, and atmospheric nitrogen deposition (with links to data and modeling activities of E. Holland and other ACD scientists). VEMAP efforts to improve ecological models to better represent land cover conversion, disturbance trajectories, and successional recovery will directly feed into CCSM Land Working Group tasks to incorporate land use and disturbance processes in the Community Land Model (CLM).

Over the next three years, VEMAP will contribute to the NCAR Initiative on Problems and Prospects in Assessment Science. This will be through ongoing development and dissemination of climate change scenarios for the U.S. from climate system models such as CCSM and of corresponding ecological change scenarios from VEMAP model experiments for use in future U.S. National Assessments and related applications.

Terrestrial carbon models, such as CLM, must incorporate and be evaluated against relevant biogeophysical and biogeochemical observations. Such observations include eddy covariance flux data, remote sensing (EOS) information, and ecosystem process data. A challenge facing the biogeosciences community is assimilating such data from a wide range of temporal and spatial scales in a manner that is internally consistent and that can then be compared with numerical models. CGD scientists and collaborators will study the climate sensitivity and coupling of carbon, water, and nutrient dynamics within a data assimilation model.

Eventually fully interactive physics, dynamics, and chemistry will be needed in order to investigate the role of various forcings on the climate of the upper atmosphere. Those forcings include: changes in solar radiation associated with the solar cycle, changes in the characteristics of upward propagation of planetary waves following climate changes in the lower atmosphere, ozone changes following ozone depletion and the effect on the radiative balance of the stratosphere, and changes in concentration of greenhouse gases.

Rasch will develop a version of the CCSM that works as an "off line climate system model" to consider a range of chemistry-climate problems. In this mode of operation, the model will be forced by observed atmospheric meteorological data, but the other components of the model will respond dynamically. This will provide the opportunity to look at problems of relevance to biogeochemistry in a more realistic environment than otherwise available. Kiehl and Rasch will explore problems including coupling between the chemical and biogeochemical environments.

Hack will carry out studies with the single column model framework, in conjunction with other idealized forms of the full atmospheric general circulation model (e.g., zonally symmetric aqua-planet configurations) to investigate spurious interactions of numerical methods with physical parameterizations. This work will include the study of physical parameterization sensitivities to vertical resolution, to changes in the large-scale forcing that come with higher horizontal resolution, to the discrete ordering of the physics parameterizations, and to the form of the upper and lower boundary conditions.

New numerical methods will be developed for global atmospheric models, and strategies will be devised to evaluate new numerical methods for that application. New test cases will be developed for baroclinic dynamical cores and standard metrics to measure success. Tests for the shallow water equations in spherical geometry will be developed which emphasize the statistics of the solution after the initial conditions are forgotten to supplement the existing standard suite of deterministic tests.

Williamson and Olson will explore methods to examine parameterizations in a deterministic evolution as is done in numerical weather prediction (NWP) without the need for a full data-ingest/analysis/forecast system. NWP centers claim that this is an excellent method of examining parameterization methods, as it allows direct comparison of parameterized variables (e.g. clouds, precipitation) with observations early in the forecast, while the forecast model state is still near that of the atmosphere.

The development of a global nonhydrostatic model for use as a dynamical core will proceed with special emphasis on extending the capability of such models to be truly multiresolution. The goal will be to study the traditionally poorly simulated aspects of the atmospheric climate simulations, such as the Indian monsoon circulation and rainfall, 30-60 day variability in the tropics, and precipitation in the Indonesian archipelago.

OCEAN AND SEA ICE RESEARCH AND MODELING

Scientists in CGD work toward understanding the large-scale ocean circulation and the dynamics of climate through studies of the important processes in the ocean and sea-ice, in air-sea-ice interactions, and in coupled systems. They also maintain and improve the ocean, sea-ice and ocean biogeochemistry components of the CCSM, through participation in the CCSM Ocean, Polar Climate, and Biogeochemistry Working Groups.

A. Achievements

Studies Using the CSM-1 Ocean Component

Significant progress was made in the areas of equatorial ocean current strength and North Atlantic gyre structure. The ingredient necessary to achieve realistic equatorial currents was found to be a lateral eddy viscosity of order 1000 m²/s acting on the meridional shear of zonal momentum. To achieve this at resolutions as coarse as three degrees, the horizontal viscosity was reformulated to be anisotropic. Thus, the along-stream viscosity can be large enough to control numerical noise, and spatially variable, so that large viscosity near western boundaries can be used to resolve boundary currents. This viscosity is a major reason for improved spatial and temporal patterns of ENSO-like variability in the tropical Pacific (Large et al., 2001). Also, in the two-degree version of the CSM ocean component, this anisotropic viscosity improved the southward penetration of the subpolar gyre off the east coast of the U.S. and the Gulf Stream separation.

A major effort was expended to construct the best possible ocean forcing over the 40 years 1958–1997. It is based on near-surface winds, temperature and humidity from the six-hourly NCEP/NCAR reanalysis, monthly satellite radiation (1983–1991) and precipitation (1979–1997). Using these fields, a 40-year hindcast of ocean variability was performed, which reproduces many aspects of the observed seasonal cycle and interannual variability. It is clearly superior to some highly smoothed analyses of historical hydrographic data, such as the World Ocean Atlas (Levitas et al., 1994) in terms of representing the recent interannual variability of the real ocean.

A series of ocean tracer and carbon cycle calculations has been completed using the CSM global ocean model. The tracer work provides valuable information on the ventilation rates of the ocean model on time scales from several years out to centuries. Simulations of deep-water chlorofluorocarbons demonstrated that the formation of Antarctic Bottom Water, in the case using the usual forcing, was weak. Significant improvements were found by modifying the surface salinity/freshwater forcing in the Ross and Weddell Seas (Doney and Hecht 2001). The carbon simulations are used to study the physical and biological factors governing the ocean inorganic carbon system, as well as links with the atmospheric and terrestrial biosphere. Doney and Lindsay have submitted results from the tracer and biogeochemical runs to the international Ocean Carbon Model Intercomparison Project. This project has a standard set of tracer simulations, and a number of new tracer simulations have been generated in the CSM ocean component over the last two years: natural equilibrium radiocarbon and abiotic carbon, equilibrium biotic carbon, anthropogenic perturbation radiocarbon and anthropogenic carbon, and chlorofluorocarbons.

Gent et al. (2001) ask the question, What sets the mean transport through Drake Passage? The paper is an analysis of 12 experiments using the CSM ocean component alone, coupled to a sea-ice model, and in fully coupled CSM mode. These experiments have a very wide range of strengths of the Antarctic Circumpolar Current and transport through Drake Passage. The conclusion is that the transport is set mostly by the zonal wind stress, or meridional Ekman transport, and by the strength of the thermohaline circulation off the Antarctic shelf. This conclusion disagrees with previous hypotheses. It is shown that the transport is definitely not set by the curl of the wind stress at the latitude of Cape Horn or by the square root of the average zonal wind stress. Both these previous theories totally ignore any effects from the thermohaline circulation.

Danabasoglu and McWilliams (2000) proposed and assessed principles for the design of an upper-ocean model, suitable for studies of large-scale oceanic variability over periods of a few months to many years. Its essential simplification compared to a conventional full-depth model is the specification of an abyssal climatology for material properties. The upper-ocean model for the general circulation is constructed based on the CSM ocean component and its solutions are compared to those of an equilibrium run of the full-depth model. The two model solutions agree well in both the mean state and short-term climate fluctuations. Therefore, the upper-ocean model is an efficient tool for studies of coupled climate dynamics, sensitivity to model parameters and forcing fields, and hypothesis testing about the role of the abyssal ocean.

Development of the Ocean and Sea-Ice Components of CCSM-2

CGD scientists continue to maintain and upgrade the ocean component of the CCSM. This work is done in very close cooperation with the ocean modeling group at LANL. Porting all the parameterizations in the CSM ocean component to the POP code is now completed, and 1 degree and 3 degree versions have been assembled for the CCSM-2. At both resolutions, it was decided to use the Gent and McWilliams eddy parameterization and the K-profile parameterization scheme for vertical mixing. This followed work which compared these to horizontal tracer eddy mixing and the Pacanowski and Philander vertical mixing scheme in a 1-degree version using POP. Ocean-alone runs clearly showed that the new schemes do a much better job in maintaining realistic temperature and salinity profiles in the upper ocean. In fully coupled integrations, the new schemes result in a much reduced climate drift and much better simulations of the areas and thicknesses of sea-ice, especially in the Arctic. This comparison of the best ocean physics to use at 1-degree resolution was a major factor that enabled the merger of the CSM and the PCM into the CCSM. The ocean component of the PCM had used 1-degree resolution with the older physics parameterizations.

The development of the new CCSM-2 sea-ice model has involved strong collaborations between NCAR, LANL, and the University of Washington. The primary dynamical improvement in the model is the inclusion of the elastic-viscous-plastic rheology to determine the force due to internal ice stress. This rheology uses an elliptical yield curve and allows the ice to resist both convergence and shear. Improvements have also been made to the thermodynamic parameterizations used in the new sea-ice model. The vertical heat conduction and storage is now solved using the formulation of Bitz and Lipscomb, which is an energy-conserving scheme that accounts for the effect of internal brine-pocket melting on surface ablation. To account for the high spatial variability that is present in the observed ice cover, the subgrid-scale ice thickness distribution of Bitz et al. is used, which allows for five ice and one open water category within each model grid cell. An active-ice-only system has been developed by Briegleb for testing the new sea-ice model. This system includes the active ice model coupled to a slab ocean model, driven by atmospheric forcing and run through the CCSM coupled system.

M. Holland has performed sea-ice variability simulations from 1958 to 1998 using the new CCSM active-ice-only system, forced by the atmospheric fields described earlier. The strength of the feedback mechanisms and the influence of various sea-ice model parameterizations on these feedbacks have been evaluated in this context. It was found that ocean mixed layer feedbacks, particularly those associated with the albedo feedback mechanism, have a strong influence on the sea-ice variability, accounting for up to 60% of the summertime sea-ice concentration and thickness variance in the central Arctic. Additionally, resolving the ice thickness distribution modifies the feedback mechanism’s impact, due to its influence on the sea-ice strength and open water formation.

Horizontal Resolution Experiments

F. Bryan and Hecht have analyzed a series of North Atlantic basin integrations at 0.4, 0.2, and 0.1 degrees horizontal resolution using the POP ocean model, (Smith et al., 2000). There is a sharp regime transition between the simulations at 0.1 and 0.2 degrees, with the representation of both the mean flow and variability becoming both qualitatively and quantitatively much more accurate. True numerical convergence of the solutions has yet to be demonstrated. An analysis of the dynamics of eddy-mean-flow interaction in the simulated Gulf Stream was initiated, including a direct comparison against corresponding analyses using dense observations obtained during the Synoptic Eddies observational program. The geographical distributions and magnitudes of mean flow and eddy energy are realistic. However, discrepancies are apparent in the spatial distribution of eddy-mean-flow energy conversions, and other measures of eddy dynamics. This may be indicative of remaining problems in simulating instability processes in the Gulf Stream, even using horizontal resolutions of order 10 km.

RMS sea surface height variability of the North Atlantic models at (a) 0.1°, (b) 0.2°, (c), 0.4° degrees resolution, and (d) an estimate based on blended ERS-Topex/Poseidon altimetric observations (Le Traon and Ogor, 1998).

Ocean Biogeochemistry

Marine biogeochemical processes related to the global carbon cycle and climate system were studied by Doney. Three paths were pursued: ecosystem modeling and remote sensing, global ocean tracer and biogeochemical modeling, and observational data analysis. A global, mixed-layer marine ecosystem model has been developed, based on extensions of a simple, nitrogen-based ecosystem model for the Sargasso Sea. The mixed-layer model was used as a testbed for evaluating and improving biological parameterizations for such things as iron limitation, zooplankton grazing, nitrogen fixation, and calcification. These ecosystem processes are thought to be critical factors in the ocean biogeochemistry and the potential future response of the marine carbon cycle to climate change (Doney, 1999). Satellite ocean color images, a proxy for surface phytoplankton distributions, play an important role in evaluating model ecosystem solutions. Doney and university collaborators have completed a statistical data analysis of the Sea-viewing Wide Field-of-view Sensor satellite ocean color images showing that the magnitude and spatial scales of variability in the biology are closely tied to those of the mesoscale physics.

Sea-Ice Variability and Thermohaline Circulation

M. Holland et al., 2001, examined the influence of simulated Arctic sea-ice variability on ice/ocean interactions and the thermohaline circulation. Under stochastic wind forcing of the ice cover, the thermohaline circulation responds with variability that is approximately 10% of the mean. This variability occurs predominantly on interdecadal time scales which are concentrated at approximately 20 years. It is forced by fluctuations in the export of ice from the Arctic into the northern North Atlantic and the subsequent variations in sea-ice melting that occur in this region. The ice melt stochastically forces the surface ocean and appears to excite a damped ocean-only mode of variability. The ice/ocean thermal coupling damps the thermohaline circulation variability, causing a 25% reduction in its standard deviation. A further study which examined how increasing atmospheric CO2 modifies these ice/ocean interactions and variability has been completed.

Improved Surface Forcing Fields

Recognizing that ocean model solutions are a function of both the model physics and the surface forcing, and that global surface wind vectors are becoming routinely observed from satellites, R. Milliff and Large have further processed these observations and used the result to force ocean models. This processing transforms the irregularly sampled satellite scatterometer data into regularly gridded wind fields. The observed statistics of wavelet coefficients are used to simulate wind components at the high resolution of 50 km globally every six hours. These wind fields have been produced from August 1996 through July 1997, covering the N-ROSS Scatterometer (NSCAT) satellite, and since the beginning of the Quick Scatterometer (QSCAT) satellite data stream in August 1999. Milliff et al., 2000, show that using these winds is essential to producing model equatorial currents that are comparable to observations.

B. Plans

CGD scientists and collaborators will continue to develop and maintain the ocean, sea-ice, and ocean biogeochemistry components of the CCSM. New developments for the ocean component will include spatial and temporal distributions of the vertical and isopycnal mixing coefficients, the use of partial bottom cells to obtain a better representation of topography, and the use of a bottom boundary layer scheme to improve the simulation of overflows. For the sea-ice component, this will include parameterizations of the ice/ocean turbulent heat exchange, lead and ridged ice processes, and surface melt ponds and their influence on the surface albedo. Scientists will also participate in evaluating the equilibrium climate and various future climate scenario integrations using the fully coupled CCSM-2.

Doney will continue to study the coupled dynamics of ocean physics – biology – chemistry with a particular focus on the natural and anthropogenically perturbed carbon cycle. The tools for this research will include the CCSM-2 ocean component, incorporating recent and to-be-developed biogeochemical modules, satellite remote sensing, and in-situ data analysis. A significant fraction of the effort will be devoted to model development and evaluation.

Holland will continue to examine the role of the polar regions in climate change and variability. The influence of the North Atlantic Oscillation on recent Arctic changes will be assessed and the feedbacks in the Arctic system will be addressed. The influence of sea-ice on interdecadal variability in the system will also be investigated. A hierarchy of models will be used in these studies, from single-column ice/ocean coupled models to the fully coupled global CCSM-2. In addition, the influence of sea-ice on paleoclimates will be examined, because feedbacks associated with sea-ice are likely to be important for the maintenance and variability of perturbed climates.

Large and collaborators will continue to gather more observational data and extend and improve the ocean hindcast, with the goal of improved understanding of mechanisms generating ocean variability. A high priority is to improve the ocean forcing in two ways. First, to extend the period of consistent satellite radiative forcing through at least 2000 to match currently available NCEP reanalysis. Second, to improve the buoyancy forcing through open leads in the presence of sea-ice by utilizing satellite measurements of the ice concentration. This high-latitude exchange is an important factor in the surface water mass transformation rates of the largest water masses of the world’s oceans.

Large will design and perform experiments to test hypotheses about the role of the ocean in generating its own variability either locally or through remote ocean pathways and about direct ocean forcing of atmospheric variability. This work requires the development of the capability to control the frequency of air-sea coupling in fully coupled model integrations. With such a tool, only specified regions need be fully coupled; others see no forcing in prescribed frequency bands, such as ENSO and the NAO, while still retaining the seasonal and higher frequency coupling required for model stability.

Bryan will extend the series of “eddy-permitting” to “eddy-resolving” North Atlantic simulations described above. Only the 0.1 degree case has a poleward heat transport that agrees with observations to within their estimated uncertainty, but experience with ocean models in the CCSM has shown that it is possible to realistically simulate poleward ocean heat transport at low resolution with adequate parameterization of the effects of mesoscale eddies. The results of these North Atlantic simulations indicate that eddy effects must still be parameterized in the “eddy-permitting” resolution regime. However, simulations at 0.4 degrees using the standard Gent-McWilliams eddy mixing parameterization have led to unsatisfactory results. While the heat transport increases to near observed levels, many of the desirable features of the high-resolution simulation, such as tightness of frontal features and eddy energy levels, are lost. In anticipation that the ocean component of coupled climate models will move into the “eddy-permitting” regime, new efforts in refining the eddy parameterizations to make them effective in this regime will be necessary.

CLIMATE DIAGNOSTICS—OBSERVATIONS AND MODEL STUDIES

CGD research has as one goal increasing our understanding of atmospheric and climate variability and climate change through parallel development and analysis of observational, assimilated, model-generated, and model-forcing data sets. The data sets are used for empirical studies, diagnostic analyses, model experimentation, and model evaluation to document variability, the processes involved, and its causes.

A. Achievements

Data Sets

A key activity is continued evaluation and development of value-added data sets. These include data sets on global atmospheric reanalyses, SST, precipitation, various satellite based products including Microwave Sounding Unit (MSU) and Outgoing Longwave Radiation (OLR), and radiosonde temperatures. Many new products derived from reanalyses are archived and made available. A data catalog, upgraded to facilitate information about and access to all Climate Analysis Section data sets, can be found at http://www.cgd.ucar.edu/cas/catalog. Other related activities were advanced under A Consortium for the Application of Climate Impact Assessments (ACACIA), which maintains data sets on model forcings and output for the community (http://www.cgd.ucar.edu/cas/ACACIA/). A data primer that details information about data sets and how to access them (Shea et al., 1994) is maintained and is available in hard copy and online (http://www.cgd.ucar.edu/cas/tn404/). These data sets are extensively used by the university community.

Major progress has occurred on development of an NCL-based software tool by D. Shea and S. Murphy for processing and visualizing data. Shea and Murphy have also provided training and performance support (http://www.cgd.ucar.edu/csm/support/), with several links to documentation and ways to process and display data. Many workshops and tutorials, including several at universities, have been held to teach students and other users how to exploit this tool.

Hurrell and Trenberth (1999) have evaluated SST global analyses, which contributed to completely new analyses by the UK Meteorological Office Hadley Centre and similar efforts in the U.S. at the Climate Prediction Center and National Climate Data Center. Hurrell et al. (2000) carried out several studies to reconcile the near-global monthly mean surface temperature anomalies with those of global MSU 2LT temperatures. They highlighted how the satellite record is affected by changes in instruments, platforms, and equator-crossing times, and they utilized MSU channel 2 data and radiosonde data to hone in on remaining problems as newer versions of the data sets were produced. Improved data sets have reduced the discrepancies between the surface and tropospheric records but indicate that most differences in trends with surface temperatures are probably real and are accounted for mostly by their physical differences and factors such as stratospheric ozone depletion.

A primary purpose in evaluating data sets is to be able to fully appreciate their strengths and weaknesses in order to exploit them to diagnose processes, transports, surface exchanges between the atmosphere and ocean or land surface, and TOA radiative forcings. Comprehensive diagnostic comparisons and evaluations have been carried out with the NCEP/NCAR and ECMWF reanalyses by Trenberth, C. Guillemot, J. Caron, and D. Stepaniak, all of CGD (Trenberth and Guillemot, 1998; and Trenberth et al., 2000). An extensive project evaluated and compared hydrological variables from various sources, including precipitable water, precipitation P, evaporation E, E-P from moisture budgets, and moisture transports. Documentation of problems and discontinuities in temperature and specific humidity fields in the reanalyses in the tropics was performed as well. Also evaluated were the vertically integrated atmospheric energy budgets. These detail the aspects that are reproducible, the likely errors, and the sources of errors. A comparison between deduced surface heat fluxes and those from the two assimilating reanalysis models (NCEP, and ECMWF) and from the Comprehensive Ocean Atmosphere Data Set (COADS) revealed substantial biases in the latter three products. Clouds are a primary source of problems in the model fluxes, both at the surface and TOA. State-of-the‑art estimates have been made of the moisture budget, freshwater fluxes, E-P, and all aspects of the atmospheric heat and energy budgets, including surface fluxes of the total energy. These have been used extensively by the community. New meridional ocean heat transport estimates have been produced (Trenberth and Caron, 2001, accepted for publication). A new description of the global monsoon and relationships with regional monsoons has also been given by exploiting the divergent circulation flow from the reanalyses.

Diagnostic Studies

A physically based conceptual framework was put forward by Trenberth (1998, 1999c, 1999d, 2000) that explains why an increase in heavy precipitation events should be a primary manifestation of the climate change that accompanies increases in greenhouse gases in the atmosphere. Increased concentrations of greenhouse gases in the atmosphere increase downwelling infrared radiation, and this global heating at the surface not only acts to increase temperatures but also increases evaporation, which enhances the atmospheric moisture content. Consequently, all weather systems that feed on the available moisture through storm-scale moisture convergence are likely to produce correspondingly enhanced precipitation rates. Increases in heavy rainfall and decreases in moderate rainfall are the consequence, along with increased risk of runoff and flooding. These changes are being observed. Because of constraints in the surface energy budget, there are also implications for the frequency and efficiency of precipitation.

The evolution of ENSO in many fields, including surface temperatures, subsurface ocean heat content, precipitation, OLR, vertically integrated atmospheric diabatic heating, and vertically integrated divergence of atmospheric energy transport, has been documented both before and after the 1976/1977 climate shift. The relationship of global warming of surface temperatures to ENSO has been determined by Trenberth and colleagues. Averaged over the year centered on March 1998, the El Niño linearly accounts for 0.17°C of the global mean temperature. Following the El Niño, the ocean gives up heat to the atmosphere to produce the delayed warming. This process is mainly important in the tropics and subtropics of the Pacific. In addition, the atmospheric circulation and cloudiness change with ENSO in such a way as to produce warming directly within the atmosphere. Much of the delayed warming outside of the tropical Pacific comes from persistent changes in atmospheric circulation forced from the tropical Pacific. Related studies by Wigley (2000) and colleagues have shown how volcanic eruptions interfered with El Niño events in their influence on surface and tropospheric temperatures. The authors devised a means to separate the relative contributions of ENSO and volcanoes to the global mean temperature record. They estimate a global mean cooling from the two volcanoes peaking at -0.2°C for El Chichon and -0.5°C for Pinatubo some 13 months after the eruption.

C. Deser (CGD) and collaborators (Deser et al., 1999) documented and modeled the observed patterns of sea-ice concentration variability in the North Atlantic and Arctic and the relation to atmospheric circulation changes, particularly the North Atlantic Oscillation (NAO). While the dominant process is that of the atmosphere forcing the changes in winter sea-ice, specifically a retreat of the ice edge in the Greenland/Barents Seas and an advance in the Labrador Sea (or vice versa), observational and modeling evidence suggests that the sea-ice changes present a weak negative feedback on the NAO and alter the local storm track adjacent to the ice edge in the Greenland Sea.

Deser and collaborators (Deser et al., 2000; Schneider et al., 1998) showed evidence that the North Pacific oceanic gyre circulation responded (with a delay of 4-5 years) to a recent decadal‑scale change in wind stress curl in a manner consistent with Sverdrup theory, confirming the first part of the Latif–Barnett hypothesis. Further work documents two events of anomalous thermal subduction in the North Pacific and traces their migration towards the equator along the ventilated thermocline pathway. However, the subducted thermal anomalies do not penetrate south of about 18N, contrary to the Gu‑Philander hypothesis. Deser and colleagues (Alexander et al., 1998, 2000) also documented the recurrence mechanism in which winter SST anomalies created by atmospheric circulation changes persist beneath the shallow summer thermocline and become re-entrained into the mixed layer during the subsequent fall and early winter, thereby “re-emerging.” This process extends the persistence of winter SST anomalies beyond the timescale associated with the thermal inertia of a fixed-depth mixed layer and can affect the winter-to-winter persistence.

Hurrell and collaborators (Hurrell et al., 2000; Hoerling et al., 2001; Marshall et al., 2001) have illuminated the NAO decadal variability and recent trends. The unprecedented upward trend in the NAO in recent decades is associated with an intensifying storm track through the Nordic seas, an increase in the atmospheric moisture flux convergence and winter precipitation in this

sector, an increase in the amount and temperature of Atlantic water inflow to the Arctic Ocean, a decrease in the late-winter extent of sea-ice throughout the European subarctic, and an increase in the annual volume flux of ice from the Fram Strait. Modeling results suggest that much of the recent upward trend in the NAO is a remote response to warming of the tropical oceans.

Dai, F. Giorgi (International Centre for Theoretical Physics), and Trenberth (Dai et al., 1998) documented the diurnal cycle of precipitation over the U.S. and how well it is simulated in models with different convective parameterizations. The models initiate convection prematurely, compared with the real world, suppressing the normal buildup of instability. Premature cloud formation inhibits the correct solar heating from occurring, further impacting the development of the continental-scale “sea breeze” and associated convergence at the surface which acts to trigger convection. Dai and several collaborators (Dai, 2001; Dai and Deser, 1999; Dai and Wang, 1999) have advanced the understanding and the description of the diurnal cycle of other variables, including surface wind, surface pressure, precipitation (frequency, amount, type) and humidity (precipitable water) and these have been used to help diagnose model deficiencies. Dai, Trenberth, and T. Karl (NCDC) (Dai et al., 1999) explored how the diurnal range of surface air temperature (DTR) is affected by clouds, soil moisture,

precipitation, and water vapor. An analysis of daily and monthly data shows that clouds, combined with secondary damping effects from soil moisture and precipitation, reduces DTR by 25% to 50% compared with clear-sky days over most land areas, while atmospheric water vapor increases both nighttime and daytime temperatures and has small effects on DTR. The well-established worldwide DTR decreases during the last 4–5 decades are consistent with the reported increasing trends in cloud cover and precipitation over many land areas.

At the request of the Pew Center on Global Climate, Wigley (1999) produced a comprehensive review of the climate change issue entitled “The science of climate change: global and U.S. perspectives” (http://www.pewclimate.org). It considered observed changes in climate, detection of an anthropogenic climate change signal, future emissions scenarios and concentration projections, and their climate consequences.

The tropospheric biennial oscillation (TBO) has been diagnosed from observations as well as global coupled model results by Meehl (Meehl and Arblaster, 1998, 2001). The importance of TBO processes in the northern spring season was highlighted. Convective heating anomalies in the southeast Asian region at that time of year contribute to the subsequent strength of the south Asian monsoon, and tropical Pacific SST anomalies undergo major transitions.

R. Madden used a 24-year time series of an index determined from satellite data to identify dates when clouds of the Tropical Intraseasonal Oscillation (Madden-Julian Oscillation) were located near the dateline. Stream function data at 300 hPa reveal Rossby wave propagation down-stream to at least the South American continent (Madden et al., 1998). The upper level anticyclone over Australia and a cyclone to its south are highly reproducible features. Madden and Shea (1999) analyzed some regional precipitation data and the surface temperature data from the NCEP/NCAR reanalysis and station data to make estimates of the potential for long-range predictability. The new results are consistent with earlier ones, with potential predictability typically small in the center of continents. Largest potential predictability is found over the tropical oceans.

H. van Loon (CGD), K. Labitzke (Free University of Berlin), and Shea have extensively documented the global influence of the 11-year solar cycle on the troposphere and stratosphere (Labitzke and van Loon, 2000; van Loon and Labitzke, 1998, 1999, 2000; van Loon and Shea, 2000). There is a clear global signal of the cycle in the global stratosphere, with the largest effect in the tropics and subtropics. In the northern winter the modulation of the solar effect by the QBO is felt as far south as the Antarctic. In the troposphere there has been a warming of about 0.2°C of the layer between 750 hPa and 200 hPa at the peaks of the solar cycle, especially in July and August.

Rainfall in the Nordeste region of Brazil is known to be highly correlated with SST anomalies in the tropical Atlantic. Saravanan and P. Chang (Texas A&M) engaged in a collaborative study of tropical Atlantic variability. They developed a Hybrid Coupled Model based on a statistical atmosphere and a coarse resolution ocean general circulation model and used this model to investigate the atmospheric response to both local SST forcing in the tropical Atlantic and remote influence from Pacific ENSO. Experiments were carried out where CCM3 was forced by observed monthly SST in the tropical Atlantic region but was coupled to a slab ocean model elsewhere. A 10-member ensemble of 45‑year integrations using this model examined the remote influence of tropical Atlantic SST anomalies. The results from this study suggested that the tropical Atlantic has a weak but statistically robust influence on the North Atlantic and European regions. They also found that interannual atmospheric variability in the tropical Pacific-Atlantic system is dominated by the interaction between two distinct sources of tropical heating: (1) an equatorial heat source in the eastern Pacific associated with ENSO, and (2) an off-equatorial heat source associated with SST anomalies in the Caribbean.

Saravanan, Deser, and G. Magnusdottir (University of California, Irvine) have investigated the predictability of the atmospheric response to centennial trends in the North Atlantic SST and sea-ice distribution. Midlatitude SST anomalies on seasonal-to-interannual time scales are rather weak, i.e., of the order of a degree centigrade. SST anomalies of this magnitude produce only a weak response in atmospheric GCMs. However, centennial trends in the SST can be considerably larger. Experiments were performed in which CCM3 was forced by midlatitude SST anomalies of the order of 5 to 10°C and also with large anomalies in the sea-ice coverage. CCM3's response to these large extratropical SST and sea-ice anomalies showed the response to centennial trends in sea-ice is much stronger than the response to the centennial SST trends, and the horizontal structure of the response has a large projection on the North Atlantic Oscillation (NAO). They also showed that the midlatitude atmospheric predictability is modest compared to the predictability associated with ENSO. This predictability arises from the atmospheric response to oceanic modes of variability, rather than from coupled modes, since there is oceanic predictability on interannual time scales but not on decadal time scales.

Saravanan also carried out a diagnostic study using the NCAR CSM that sheds some light on the mechanisms of midlatitude climate variability. A hierarchy of GCM integrations was analyzed in the study, corresponding to different degrees of coupling between the ocean and the atmosphere the 300-year coupled integration using the CSM being at one end of the hierarchy of experiments and uncoupled CCM3 integrations forced by the climatological annual cycle of SST being at the other end. At each level of the hierarchy, the simulated atmospheric low frequency variability was compared to the low frequency variability in the NCEP/NCAR reanalysis data. The quality of the simulations improved with the increasing degree of coupling. The uncoupled CCM3 integration captured the spatial structure of variability but not the amplitude. The spatial patterns of atmospheric low frequency variability in the coupled climate system are essentially the same as those in the uncoupled atmosphere. Coupling to an interactive ocean simply alters the amplitudes of the different modes of atmospheric variability. The patterns of surface heat flux associated with the dominant modes of atmospheric low frequency variability, the Pacific North American pattern, and the NAO, were also analyzed in this hierarchy of CSM and CCM3 integrations. The surface heat flux patterns show a close correspondence to observed spatial patterns of SST variability in the midlatitudes, indicating that stochastic low frequency variability in the atmosphere may be the primary mechanism behind observed midlatitude climate variability.

Saravanan, Danabasoglu, Doney, and McWilliams have carried out a study of the relationship between temperature and salinity variations on decadal time scales. The primary data set for this research is a long control run of a coupled ocean-atmosphere model, with a simplified two-level atmospheric model and an Atlantic-like sector ocean model. Dynamical aspects of the variability in the simplified representation of the climate system were analyzed in an earlier study, which identified oscillations of a decadal time scale. In the continuation of this study, thermodynamic and tracer-related aspects of the variability have been analyzed. Results show that positive correlations between temperature and salinity are a ubiquitous feature of decadal oceanic variability. Although these correlations are relatively weak at the ocean surface, they increase dramatically with increasing depth. It can be established that these correlations are not due to atmospheric forcing but clearly due to some oceanic mechanisms.

One process that strongly influences the behavior of prominent seasonal anomalies is the feedback from fluxes produced by synoptic transients. G. Branstator has examined the relationship between eddy momentum fluxes and low-frequency circulation anomalies in CCM0. Using analog techniques, he has found that about 50% of the feedback variance can be explained by the time-average state, and he has discovered that the relationship between the average state and eddy flux convergences is nearly linear. Together, these facts mean that a simple linear operator found from regression can be used to represent the complex interplay between low-and high-frequency transients.

Branstator has carried out a three-pronged study that seeks to elucidate properties of variability on interannual time scales during all seasons of the year. The first part of this investigation quantifies the basic properties of interannual variability as a function of season and finds that there is a distinct seasonal cycle of amplitude, spatial scale, and structure for monthly and seasonal anomalies. Using a stochastically excited barotropic model, the second component has discovered that, for the most part, the observed features described by the first part of the study are the result of the influence of the seasonally dependent mean state on circulation anomalies. This is consistent with another observational finding of the study, namely, that there is a strong anticorrelation between the pattern of vorticity flux divergence resulting from interannual flow anomalies and the pattern of climatological waves, which is an indication that the anomalies are reacting to each season's mean state. The third part of this study of seasonality (undertaken with J. Frederiksen, CSIRO) has determined to what degree the eigenmodes of the system are affected by slow, seasonal variations in the mean state. The main effect of temporal variations in the background state turns out to be an enhancement in growth rates during early spring.

Because of strong intrinsic atmospheric variability, it is difficult to estimate the true strength of the atmospheric response to El Niño. To address this problem Branstator has used an ensemble of 45-year CCM3 integrations and found that there is about a 90% chance that CCM3's response to El Niño is too weak. Diagnostic work indicates that misplacement of the longitudinal position of the tropical rainfall anomaly induced in the model is probably contributing to the weak response. Another factor, suggested by joint work with T. Chen (Iowa State University), may be the misrepresentation of a secondary wavetrain that often emanates from the western Pacific during ENSO events.

B. Plans

Data sets

The CAS data catalog will continue to be updated and developed with new interfaces to enable data access and requests. New features will include development of a web-based data catalog of historical data sets and related documentation to facilitate access and knowledge for interdisciplinary studies of climate variability. CAS will also facilitate access to web-based metadata and data, and limited processing and visualization, currently developed as a Community Data Portal by SCD based upon DODS (Distributed Oceanographic Data System), the Live Access Server (LAS), and Ferret (NOAA PMEL based). A preliminary framework is the ACACIA Regional Climate data Access System (ARCAS), please see http://dataserver.ucar.edu/arcas‑bin/ARCAS. The NCL‑based processor tool will develop further to handle the CCSM POP grids, integrate Java, python, and NCL into a various web-based data access and visualization tools, and contain upgraded visualization and learning tools. In addition we plan to hold further “Data Processing and Visualization” tutorials and workshops at both NCAR and at universities.

NCAR is participating as a full partner in the ECMWF 40-year reanalysis (ERA-40), which will enable the reanalyzed data to be brought to NCAR and made available to the research community (including university and federal researchers) without restriction. The basic mission is to carry out consistency checks on the budget of the mass of dry air, the moisture budget, and the heat and energy budgets, with an emphasis on influences on temperatures. Comparisons will be made with results from NCEP reanalyses for the same times.

Diagnostics

The foremost ingredient for precipitation variations, and one that has not had adequate attention paid to it, is the source of the moisture. From a climate perspective, the intensity of precipitation when it falls and its frequency are of as much concern as amounts, since these factors determine the disposition of rainfall once it hits the ground and how much runs off. Most precipitation comes from moisture already in the atmosphere at the beginning of the storm that provides the mechanisms for the moisture to precipitate out, and transport by the storm-scale circulation into the storm is vital. However, whether a thunderstorm, an extratropical cyclone, or a hurricane, the storm-scale circulation feeds upon the background prevailing moisture amounts, which are determined by larger scales. An excellent example is the diurnal cycle of precipitation, whose correct simulation remains an unsolved challenge. Diagnostic computations will explore these aspects.

There are questions concerning the effects of specifying bottom boundary conditions in atmospheric GCM simulations. Future work will focus on an analysis of experiments from a GCM run in both coupled and uncoupled mode. For the latter, SST and sea-ice from the coupled run are specified at each model time step. Integrations, started from slightly different atmospheric initial conditions, will provide an ensemble from which the statistical aspects of the atmosphere can be compared to those from the fully coupled experiment. Several analyses will continue toward documenting and evaluating CCSM results.

Recent work has shown that the trend in Atlantic climate since 1950 during boreal winter is linked to a progressive warming of tropical SSTs. During boreal summer, pronounced decadal changes in pressure and rainfall over the North Atlantic and Europe are statistically related to changes in rainfall over the tropical Atlantic and North Africa. The dynamics of these apparent teleconnections are poorly understood, however. Using both observations and a suite of experiments performed with different GCMs, the role of tropical forcing in producing North Atlantic climate variability throughout the annual cycle will be examined. Because circulation variability in the North Atlantic sector is seasonally dependent in both space and time, we propose to develop a monthly NAO index that takes into account the seasonal variation in circulation anomalies by using a new technique termed “cyclostationary EOF analysis.” The monthly NAO index will have application in climate impacts and paleoclimate studies. The causes of Arctic sea-ice cover retreat, which is strongest in summer during recent decades, will be explored using the hypothesis that the wintertime atmospheric circulation trends over the Arctic associated with the NAO/AO patterns are the main cause of the summertime ice retreat through their impact on wintertime ice thickness, which then preconditions the ice pack for accelerated melt during summer. We propose to test this hypothesis with a set of carefully controlled numerical experiments in which we force the sea-ice field with atmospheric circulation anomalies during specific times of the year.

An ongoing research objective is to improve the description of the global heat budget in the atmosphere and ocean, including the variability and trends, and implications for surface temperatures and precipitation. To achieve this end, we will comprehensively analyze global data sets, especially the “reanalysis” data sets. Changes in storm tracks and their relationship to leading patterns of climate variability will be examined as a function of season. The diagnostic results will be used to better determine the role of adiabatic processes in the El Niño phenomenon, and thus the role of El Niño in climate and how it may change with global climate change. Basic data sets will be generated that describe the mean annual and diurnal cycles, and the interannual variability of the global atmospheric circulation and the associated changes in the upper ocean. Similarly, we will develop improved descriptions of the global hydrological cycle in all its facets, including the ocean fresh water budget. Results should be useful for model verification and for improving models.

A particular project is to analyze the global monsoon energetics and atmospheric energetics in detail. Atmospheric energy transports are primarily carried out by transient baroclinic weather systems in the extratropics assisted by the quasistationary planetary waves in the Northern Hemisphere winter. Large-scale overturning circulations, of which the Hadley cell is most prominent, dominate the transports in low latitudes. This therefore raises key questions about the role of the transients and heat transports by the largely horizontal motions in driving the Hadley circulation. Diagnostic computations using reanalyses will be used to examine these aspects. Further studies of the TBO are planned that will include analyses of low-level winds in answering two questions about the TBO: why is March-April-May a crucial transition season? and what makes the TBO transition in the Pacific? These will utilize both analyses and model simulations.

SST anomaly persistence in midlatitudes is directly related to the depth of the upper ocean mixed layer by sequestering the anomalies within the summer seasonal thermocline and re-entraining them into the following winter’s mixed layer. As well as documenting the observed persistence characteristics of SST anomalies in midlatitudes, an extension of the “Hasselmann” model, which incorporates the seasonal cycle of mixed layer depth (specifically, the entrainment process), will be used to interpret the observations within this simple physical framework. An entraining mixed layer is a more relevant “null hypothesis” for SST variability in midlatitudes than a nonentraining one. The debate over the origin of interdecadal climate variability in the North Pacific and North America focuses on the extent to which it is forced by the tropics versus generated by ocean-atmosphere interaction within the extratropics. We will use historical climate records to document the spatial and temporal patterns of interdecadal variability spanning the Indo-Pacific region and rely on physical consistency among different parameters for verification of climate signals in the early portion of the record. Preliminary results suggest that the tropics may play a key role in the interdecadal climate variability over the North Pacific/America; however, the spatial patterns of the tropical variability are distinct on interannual vs. interdecadal time scales.

Multivariate methods in the detection of climate change will be explored by examining: (1) the effects of previously unquantified and unexamined historical anthropogenic forcings, in particular historical land-use changes; organic and black carbon (soot) aerosols from fossil fuels and biomass burning sources; and changes over time in the spatial distribution of SO₂ emissions and atmospheric sulfate aerosol loadings; (2) detectability of the effects of specific climate mitigation strategies in the future; and (3) the effects of anthropogenic forcing on natural modes of variability. Low-frequency variations in ENSO teleconnections will be explored by focusing on natural (unforced) changes in the character of ENSO and its teleconnections (i.e., the noise against which any anthropogenically induced changes in ENSO signals must be identified). A major component of this work will be directed towards better documenting and understanding the way ENSO’s teleconnection patterns have changed in the past. A striking manifestation of this is the apparent instability in the relationship between global mean temperature and any ENSO index. Model results will be used to better understand the primary driving forces for ENSO-related atmospheric teleconnection changes and their relationship to, for example, other modes of variability (such as the Pacific Decadal Oscillation).

PREDICTABILITY OF WEATHER AND SHORT-TERM CLIMATE VARIABILITY

The past, present, and future research directions in this area can be grouped into three main topics: 1) the use of linear methods in analysis of nonlinear systems, 2) the quantification of uncertainty in highly nonlinear atmospheric systems, and 3) the theory and utility of stochastic modeling applied to the climate system.

A. Achievements

Use of Linear Models in Studies of Predictability and Sensitivity

R. Errico (CGD) has been at the forefront of the development of adjoint tools, including an adjoint limited area dynamical core Mesoscale Adjoint Modeling System (MAMS) and the tangent linear and adjoint forms of various physical processes. Errico and K. Raeder (CGD) have produced a new version, MAMS2, which was used at the Naval Research Laboratory (NRL, Monterey) to develop observation targeting strategies. Adjoint model applications have included: 1) development and validation of a useful adjoint model including moist physics, 2) examination of atmospheric stability and predictability using singular vector decomposition (Errico, Raeder, and M. Ehrendorfer [University of Vienna]), 3) examination of the relationships between Lyapunov vectors, bred modes, and singular vectors (Errico, R. Langland, R. Gelaro, and C. Reynolds [NRL-Monterey]); and (4) synoptic studies (Errico, Raeder, J. Lewis [DRI-Reno], and L. Fillion [RPN-Montreal]).

Adjoint models often produce new and unexpected, but confirmable, results that sometimes require new paradigms. Some of the most interesting results produced in collaboration with CGD members include: 1) forecast barotropic vorticity in cyclones is sensitive to initial moisture perturbations, 2) consideration of moist physics produces leading singular vectors with distinct structures compared with their dry counterparts, or at least significantly increases growth rates, 3) although energy-norm singular vectors are predominately dynamically balanced, they have ageostrophic components that are significant because the two types of structures can evolve into nearly identical structures, 4) the size of the subspace of unstable structures is a few percent of the entire model phase space, 5) measures of the sensitivities of forecast precipitation rates vary much less as longer forecast periods are considered compared with sensitivities of barotropic vorticity; and 6) long-term growth of Lyapunov vectors can be explained by a few leading, short-term singular vectors.

The quantification of uncertainty in highly nonlinear atmospheric systems

D. Baumhefner (CGD), Errico, and Tribbia conducted experiments with several versions of CCM to evaluate how differences in synoptic-scale predictability error growth (PEG) affect the ensemble mean properties of prediction. The forecast skill of individual forecasts and ensemble mean forecasts of CCM3 were compared at three resolutions, T42, T63, and T106. Thirty-two ten-member cases were used to evaluate differences in the skill of individual forecasts and the skill of the ensemble mean forecasts. Little difference was seen in the skill of the individual forecasts, but significant differences were exhibited in the skill of the ensemble means, which increased with increasing model resolution. This coincides with the progressive increase in PEG in the 0-2 day range with increasing resolution demonstrating that a representative, accurate depiction of forecast uncertainty is necessary for accurate prediction of forecast reliability and to realize the nonlinear filtering benefits of ensemble prediction. They also analyzed PEG in the perfect data, imperfect model framework. Models with differing horizontal resolution (T42, T63, T106, and a T170 control) were integrated with identical initial states in the scales that are resolved in common. Error growth then enters the system through the inverse cascade of variance from unresolved scales into resolved scales.

Baumhefner also addressed the question of ensemble sensitivity to different types of initial perturbations. Samples of the NCEP MRF (Medium-Range Forecast Model) operational ensemble forecasts (11 members at T62 resolution) and ECMWF operational ensemble forecast system (33 members at T63 resolution) made daily for the winter of '95-'96 were collected and analyzed. Cases were selected from this set and rerun with the NCAR CCM3 model ensemble system. The NCEP system uses a "bred mode" perturbation, the NCAR system uses an analysis difference simulator, and ECMWF uses singular vector decomposition. The forecast skill of the three systems was analyzed. The dispersion of all ensembles was very similar, indicating the method of perturbation was not an important factor.

Baumhefner and Tribbia continued research on seasonal forecast skill, concentrating on a forecast comparison project in which several models were to be tested for skill in the three-month time frame. Sixteen winter cases were run with ten member ensembles using CCM3. These forecasts were all forced by observed SST's. The seasonal skill of these runs was evaluated and various methods of systematic error removal were tested. The forecast midlatitude patterns of flow were, on average, not very skillful; however, in 6 of the 16 cases, the skill was quite good. The probability distributions of the ensemble as defined by the individual member forecast values of the PNA index always included the observed value. The PNA index scores showed an intriguing long-term memory of the initial state.

The theory and utility of stochastic modeling applied to the climate system

Branstator developed a barotropic linear model of the atmosphere designed to represent all of the linear dynamical processes affecting atmospheric evolution by using an empirical approach in which the dynamical equations are formulated to reproduce the atmosphere's dynamics as observed in a long record of historical behavior. The model has been verified by finding that it accurately reproduces the response of a GCM to equatorial heating anomalies. Branstator has been able to determine that even though the state variable in his model is barotropic streamfunction, implicit in its dynamics are the effects of divergence anomalies and of feedbacks from momentum fluxes associated with high-frequency transients, two processes not represented in conventional linear models.

Branstator also produced a multilevel, multivariate version, which has proven to be more accurate than the barotropic version at approximating GCM solutions. Branstator and A. Gritsoun (Russian Academy of Sciences) have applied the fluctuation-dissipation theorem to generate an empirical model of the response of the atmosphere to external forcing.

Branstator, J. Berner (University of Bonn and ASP) and C. Tebaldi (GSP) investigated the phase space behavior of extended integrations of NCAR's CCM0. Their work indicates that in a few directions in phase space, probability density functions of CCM0 states are distinctly nonGaussian. Furthermore, plots of nearby trajectories indicate that there are multiple stagnation points in the phase space. The distribution of states in phase space can be largely reproduced simply by considering a dynamical system composed of a deterministic term that consists of the observed mean velocities as a function of phase space position and a stochastic term that is position independent. Nonlinearities in the deterministic term are crucial in reproducing the CCM0 Probability Density Function (PDFs) in those directions where the PDFs are nonGaussian.

B. Plans

Future plans regarding adjoint model development and application include: 1) further development of techniques to produce useful adjoints of physical parameterization schemes; 2) investigation of dynamic balance issues affecting precipitation forecasts and data assimilation of precipitation observations; 3) encouragement of others to use adjoints, including MAMS, as a tool to investigate hypotheses in synoptic meteorology; 4) investigation of adjoint-derived forecast sensitivities with respect to analyzed observations using the adjoint of a data assimilation system; and 5) further investigation of singular vectors with regard to moist norms.

Future diagnostic analyses and theoretical studies will continue to focus on the nature and sustenance of the leading structures of variability. The question of why similar structures are responsible for atmospheric variability from monthly to decadal time scales will continue to be explored theoretically. The role of high-frequency transients in variability will be analyzed and their influence on low-frequency anomalies will be studied through a parameterization of their effect in linear planetary wave models. The importance of multiple equilibrium states in determining the preferred patterns of both intrinsic and forced atmospheric variability will be studied using both diagnostic and mechanistic modeling approaches. A heightened emphasis will be put on decadal variability in the North Atlantic and North Pacific and its relationship to tropical ocean variability.

There will be an increasing use of the mathematical formalisms of stochastic modeling on a wide variety of fronts. Simple models of flow dependence in error covariances will be developed for use in both data assimilation and uncertainty prediction. For the diagnostic understanding of covariability and coupling in the climate system, theoretical formalisms related to the fluctuation-dissipation relationship in statistical mechanics will be invoked and studied as to its utility as a guiding principle and to develop hypotheses regarding the dynamical explanation of climate variability.

C. Activities in Response to the Previous Review

The previous review panel gave 14 recommendations for CGD. These recommendations are summarized below, together with our responses to those recommendations.

“The Panel urges CGD to formulate a scientific plan that includes specific scientific objectives.” CGD held a retreat to begin the development of a plan and a follow-up meeting in April, 1997, to continue the process. The CGD Strategic Plan may be found at http://www.cgd.ucar.edu/98plan.html. The CCSM plan can be found at http://www.ccsm.ucar.edu/management/plan2000.

“We recommend a comprehensive evaluation and diagnosis of CSM output in order to optimize the scientific value of CSM…” CAS, with numerous collaborators, has participated vigorously in work on CCSM diagnosis and evaluation. Examples include Meehl's work on factors that affect the amplitude of El Niño in coupled models, the role of anthropogenic forcing in sensitivity experiments of 20th and 21st centuries climates, and analysis of the tropospheric biennial oscillation; Trenberth's work on the simulation of the diurnal cycle in precipitation and other variables and state-of-the-art estimates of atmospheric heat and energy budgets; Hurrell's work on the forcing mechanisms of NAO variability and work with Shea on an evaluation of the planetary wave structure and precipitation distribution in potential new atmospheric components of CCSM; and Deser's work on sea ice variability and its relation to atmospheric circulation changes. Scientists from CAS, primarily Meehl and Hurrell, but also others, have participated vigorously in work on CSM evaluation. Other scientists from CGD and the community have also participated in a wide variety of diagnostic activities.

“An additional requirement for the optimization of CSM’s scientific value is entrainment into CSM of non-NCAR collaborators…” We have worked hard and, we believe, effectively to entrain a wide community of collaborators into the CCSM activity. Please refer to the CCSM web site (http:www.ccsm.ucar.edu) to see the management structure, the working group structure, the workshops and the list of papers for evidence that there is an active community involved in CCSM.

“NCAR and non-NCAR scientists should collaborate in providing coordination of scientific uses of CSM…” See the previous answer.

“The Panel recommends a single flexible framework for each CSM component in order to further enhance CSM’s scientific value…” We have worked to make all components of the model easier for non-NCAR scientists to work with. CGD has played a major role in the Common Model Infrastructure Project, a self-funded, self-organized attempt to make model components interchangeable. NCAR was asked to take the lead in a proposal to NASA to develop a flexible framework for model components. Some of our collaborators are from GFDL, MIT, and NASA/GSFC. CGD and several DOE laboratories are collaborating in the DOE CCSM Avant Garde Project, in which DOE software engineers are working with CGD and other software engineers to improve the portability, flexibility and performance of the model. Avant Garde participants are also working on a Coupled Model Toolkit and designing the next-generation coupler. A CCSM Software Engineering Working Group has been formed to help with the software development for CCSM-2. Further work is needed, but we are well on the way to implementing this recommendation.

“CGD should continue its development of RegCM in order to support high-resolution climate reconstructions and to contribute to quantitative assessments of detailed regional climate change predicted by GCMs…” Filippo Giorgi was working on putting CCM3 physics into the RegCM, and had largely completed the task, when he was offered a job in Italy. Filippo took a one-year leave and towards the end of that time decided that he wanted to stay in Italy. We have not replaced Filippo, partly due to lack of funds, but also because we have chosen to build up CGD in other fields, such as biogeochemistry. We maintain some contact with Filippo and he continues to make his model available to some of the collaborators he had when he was at NCAR.

“A mechanism should be developed for the coordination of regional assessment activities both within NCAR and at universities and regional climate centers.” With Filippo’s departure, most of the action on regional assessment activities is now elsewhere. Tom Wigley is the person in CGD most involved in that activity now.

“Stronger collaboration with MMM and ACD (and perhaps ESIG) will also benefit the development of CSM…” We are collaborating with MMM in the Clouds and Climate Program and with ACD on the Whole Atmosphere CCM Project. We have had discussions with Danny McKenna, the new ACD Director, about future collaborations. McKenna has become a member of the CCSM Scientific Steering Committee to help facilitate that collaboration.

“The Panel strongly endorses staffing of CSM positions to facilitate access to CSM by non-NCAR users…” Thanks to the support of NSF, in particular Jay Fein, Herman Zimmerman and Michael Ledbetter, money has been made available for several community liaison positions in different areas of CCSM‑coupled model data, atmosphere model diagnostics, ocean model, land model, sea ice model and paleoclimate model.

“There is a need for new mechanisms to attribute the development of CSM modules and subroutines to scientists who have invested their time and effort in such activities…” We have found that the working groups are good places for scientists to present and test their ideas and get the recognition they deserve for their activity. At this summer’s CCSM Workshop, we will award the first CCSM Distinguished Achievement Award to someone who has made a significant contribution to the CCSM.

“The Panel recommends that, when hiring is possible, strong consideration be given to the Scientist I and II levels…” In the past 5 years, CGD has hired 4 Scientists II, Clara Deser, Bill Collins, Bette Otto-Bliesner, and Tim Kittel, and one Scientist I, Marika Holland.

“Mechanisms for the recruiting, mentoring and retention of young scientists, particularly female scientists, should be implemented by CGD…” In addition to the progress mentioned in the response to the previous recommendation, the CGD Director has co-chaired an NCAR-wide Diversity Task Force that has authored recommendations concerning recruitment, mentoring and retention of young scientists. The American Physical Society had a panel visit NCAR recently to examine these issues. We have responded positively to its report. Mentoring of young scientists has become a much more important aspect of our activities recently.

“It is imperative that the effectiveness of CSM governance be closely monitored, especially from the perspective of non-NCAR scientists whose active participation is essential to the success of CSM.” The CGD Director periodically discusses the operation of the CAB, the SSC and the Working Groups with the NSF Program Manager, the President of UCAR and the NCAR Director. We discuss what is going well, what needs improvement and what extra should be done. At present, we are happy with the functioning of the CCSM management and governance.

Institutional Responses to the recommendations from the 1996 program review

The last review of NCAR Programs in 1996 resulted in several recommendations for the Center as a whole. While some of the actions that were taken in response to these recommendations are more appropriate for inclusion in the upcoming NCAR-wide management review, there were a number of actions that were taken on behalf of or by all the divisions that merit discussion here.

The 1996 review pointed to issues of balance between early and late career scientists, the mentoring and professional development of scientific staff, especially of women and other underrepresented groups, and diversity. In response, NCAR has made a concerted effort to emphasize mentoring and professional development for all staff. A set of guidelines were developed and made available to all staff (http://www.ncar.ucar.edu/Values/mentoring.html). These guidelines have been reinforced with the requirement that five year professional development plans be developed for all staff in conjunction with their annual performance evaluations. In addition, all NCAR staff participate in regular mandatory sexual harassment awareness training program.

NCAR has sought to increase the number of early career scientists through a special, on-going program of recruitment. These new hires are being coordinated by the Advanced Study Program and will be funded by a combination of UCAR, NCAR-wide, and division funds. Four new hires are being made in 2001, with an additional four slated for early FY2002. This will be an ongoing program until the desired balance among the scientific staff is achieved. This effort, coupled with the UCAR policy which allows for negotiated early retirement, and other hiring programs, is already having a beneficial impact on the demographic balance at the center.

In July 2001, the American Physical Society's Committee on the Status of Women in Physics was invited to NCAR to examine the professional climate for women scientists at the center. The process involved the evaluation of anonymous responses to questionnaires, group and individual interviews with scientific and technical staff and the development of recommendations. The issues examined included compensation, promotion policies, career development, and family responsibilities. The APS report cited the high quality of the work environment and scientific program at NCAR and also made several important, specific recommendations for improvements that are being implemented. These include: a review of the project scientist and associate scientist tracks, a formal mentoring program, and new venues for more effective communication.

A second issue raised in the 1996 review involved the need to coordinate strategic planning across the divisions. In response to this finding, each of the divisions developed a plan that outlined their research and technology directions for the future. These plans identified how these activities supported and advanced the overall center’s strategic goals and priorities. In addition, each division established an external advisory committee comprised of members of the university and research community at large. The divisional advisory committees attend annual meetings with division management, participate in division retreats, and serve in a number of capacities.

The 1996 review raised the issue of more effective communication across the institution, particularly on administrative and personnel matters. NCAR has responded vigorously to this recommendation and continues to address communication needs through a wide variety of mechanisms including annual retreats and “town meetings,” periodic divisional “all hands” meetings, monthly management meetings and numerous web-based information sources that span the full administrative and programmatic spectrum. One-on-one interactions between supervisors and staff will be increasingly emphasized through development of the annual professional development plans and a formal mentoring program.

Finally, the 1996 review pointed to the need to establish incentives for cross-divisional activities as a way of encouraging broad interaction across divisions and disciplines. NCAR has initiated several mechanisms for fostering cross-divisional programs, including the establishment of an opportunity fund focused on interdisciplinary projects. This fund has already seeded several successful inter-divisional efforts (for example, the Whole Atmosphere Coupled Climate Model, WACCM, and the NCAR Biogeosciences initiative). NCAR has emphasized its support for several programs outside of the traditional divisional structure, including the Geophysical Statistics Program, which is supported by the Math and Physical Sciences directorate at NSF, and the Geophysical Turbulence Program, headed by Dr. Annick Pouquet. In addition, there are several major cross-divisional programs funded from the U.S. Global Change Research Program and the U.S. Weather Research Program. These integrated programs are listed in Section IV: Linkages, of this document.

D. Equipment

To accomplish our research, we use computers heavily. These range from desktop computers and terminals to the large machines in SCD and elsewhere. The CGD Computing Facility supports the division's computing needs. This includes the central servers, the typical file, print and e-mail services, FTP and Web servers for information distribution internally and to communities outside of CGD, tape drives, CD-ROM drives and CD burners.

The Computing Facility includes eight server computers servicing 175 desktop computers for a local user population of 120 people. This includes two primary file servers, two dedicated compute servers, one server for external access, one terminal server and an information server.

The new terminal server implements a change in desktop computing strategy in which older computers are replaced by thin clients, which increases the price/performance ratio while developing a better scheme for the maintainability of the hardware. The new desktop thin client devices are serviced by a Gigabit Ethernet connection on their server.

All networked devices are now or soon will be connected at 100 Megabit Ethernet, while the network configuration within CGD is being simplified to enhance reliability in collaboration with the SCD Networking Group.

Each year the division buys equipment to keep our systems up to date. Purchases include thin client systems, servers, storage devices, and printing solutions.

IV. LINKAGES TO OTHER GROUPS

To help advance their research, CGD scientists often collaborate with scientists at universities and other institutions by having them visit NCAR for a day or over a year. This collaboration extends the field of scientific knowledge at NCAR. Collaboration is evident in almost all our areas of research and in developing our models. Our future plans are for increased collaboration on the final development of the CCSM and the use of the model for exploring climate research areas. Listed are some of our most recent collaborators and the universities or institutes with which they are affiliated.

A. Affiliate Scientists

Donner, Leo; Geophysical Fluid Dynamics

Laboratory/NOAA

Farrell, Brian; Harvard University

Haidvogel, Dale; Rutgers University

Semtner, Albert; Naval Postgraduate School

Stevens, Bjorn; University of California at Los Angeles

Zender, Charles; University of California at Irvine

B. University Visitors and Collaborators

(includes students)

Alley, Richard; Pennsylvania State University

Ammann, Caspar; University of Massachusetts

Andrews, John; University of Colorado

Baer, Ferdinand; University of Maryland

Bailey, Barbara; University of Illinois

Barlow, Lisa; University of Colorado

Barron, Eric; Pennsylvania State University

Battisti, David; University of Washington

Bellone, Enrica; University of Washington

Bengttson, Thomas; University of Missouri

Berliner, Mark; Ohio State University

Bickel, Peter; University of California at Berkeley

Bitz, Cecilia; University of Washington

Bretherton, Chris; University of Washington

Cess, Robert; State University at New York, Stony Brook

Chang, Ping; Texas A&M University

Chelton, Dudley; Oregon State University

Dargaville, Roger; University of Alaska

Das, Barnali; University of Washington

DeConto, Robert; University of Massachusetts

Dickinson, Robert; Georgia Tech

Dupigny-Giroux, Leslie-Ann; University of Vermont

Ewald, Brian; Indiana University

Fournier, Aime; University of Maryland

Fung, Inez; University of California at Berkeley

Ghil, Michael; University of California at Los Angeles

Grossman, Daniel; University of Colorado

Hamilton, Lawrence; University of New Hampshire

Higdon, David; Duke University

Hoffert, Martin; New York University

Huber, Matthew; University of California at Santa Cruz

Jablonowski, Christiane; University of Michigan

Jayne, Steve; University of Colorado

Jennings, Anne; University of Colorado

Johns, Craig; University of Colorado at Denver

Jones, Richard; University of Colorado Medical Center

Kaplan, Alexey; Lamont-Doherty Earth Observatory at

Columbia University

Krishnamurti, T.N.; Florida State University

Kutzbach, John; University of Wisconsin at Madison

Lima, Ivan; Rosenstiel School of Marine and

Atmospheric Science, University of Miami

Loschnigg, Johannes; International Pacific Research Center, Honolulu, Hawaii

Mahowald, Natalie; University of California at Santa Barbara

Mechoso, Carlos; University of California at Los Angeles

Meiring, Wendy; University of California at Santa Barbara

Morgan, M. Granger; Carnegie Mellon University

Mullen, Steve; University of Arizona

Nevison, Cindy; University of California at San Diego

Ogilvie, Astrid; University of Colorado

Ojima, Dennis; Colorado State University

Oleson, Keith; University of Colorado

Orlando, Wendall Welch; Yale University

Polvani, Lorenzo; Columbia University

Prusa, Joseph; Iowa State University

Qian, Jian-Hua (Joshua); Lamont Doherty Earth Observatory at Columbia University

Ramanathan, V.; Scripps Institution of Oceanography at University of California at San Diego

Raphael, Marilyn; University of California at Los Angeles

Sang-Ik, Shin; University of Wisconsin at Madison

Schlesinger, Michael; University of Illinois at Champaign

Shumway, Robert; University of California at Davis

Slater, Andrew; University of Colorado

Sloan, Lisa; University of California at Santa Cruz

Smith, Laryn Micaela; University of Colorado

Smith, Richard; University of North Carolina

Streett, Sarah; Colorado State University

Tebaldi, Claudia; Duke University

Temam, Roger; Indiana University

Upchurch, Garland; Southwest Texas State University

Wallace, Mike; University of Washington 

Walsh, John; University of Illinois

Weiss, Jeff; University of Colorado

Weyant, John; Stanford University

Wikle, Chris; University of Missouri

C. Other U.S. Government Agencies

Caldeira, Ken; Lawrence Livermore National Laboratory/DOE

Duffy, Philip; Lawrence Livermore National Laboratory/DOE

Edmonds, James; Pacific Northwest National Laboratory/DOE

Holland, David; U.S. Environmental Protection Agency

Klein, Stephen; Geophysical Fluid Dynamics Laboratory/NOAA

Larson, J. Walter; Argonne National Laboratory/DOE

Smith, Steven J.; Battelle Pacific Northwest Laboratories/DOE

Smith, Richard; Los Alamos National Laboratory/DOE

Solomon, Susan; NOAA

Stouffer, Ronald; NOAA

Taylor, Karl; Lawrence Livermore National Laboratory/DOE

D. Industry/International

Aimin, Ma; Chinese State Development Planning Council, People's Republic of China (PRC)

Behrens, Jorn; Munich University of Technology, Germany

Brown, Simon; Hadley Centre, United Kingdom

Bugmann, Harald; Potsdam Institute for Climate Impact Research, Germany

Buizza, Roberto; European Centre for Medium-range

Weather Forecasts, United Kingdom

Burridge, David; European Centre for Medium-range

Weather Forecast, United Kingdom

Cuihua, Sun; Office of the National Coordination Committee for Climate Change, PRC

Crutzen, Paul; Max-Planck Institute for Chemistry, Germany

de Koningh, Maarten; KEMA, The Netherlands

Derome, Jacques; McGill University, Canada

Dickson, Robert; Centre for Environment, Fisheries and Aquaculture Science

Ehrendorfer, Martin; University of Vienna, Austria

Gregory, Jonathan; Hadley Centre, United Kingdom

Guide, Jia; Environment Division, Chinese Foreign Ministry, PRC

Haedrich, Richard; Memorial University of Newfoundland

Haine, Thomas; University of Oxford, United Kingdom

Hakkarinen, Charles; EPRI

Harvey, L. D.; University of Toronto, Canada

Henderson-Sellers, Ann; Australian Nuclear Science and Technology Organization, Australia

Huerta, Gabriel; Centro de Investigacion en Matematicas (CIMAT), Guanajuato, Mexico

Ioannou, Petros; University of Athens, Greece

Jolliffe, Ian; Kings' College, University of Aberdeen, United Kingdom

Kergoat, Laurent; Centre National de la Recherche Scientifique, France

Labitzke, Karin; Free University of Berlin

Lempert, Robert; RAND

Lew, Debra; National Renewable Energy Laboratory

Lin, Dai; National Renewable Energy Laboratory

Lloyd, Matt; Cambridge University Press

Lynch, Peter; Met Eireann, Dublin, Ireland

Maruyama, Koki; Central Research Institute of Electric

Power Industry (CRIEPI), Tokyo, Japan

Medvedev, Alex; University of Toronto, Canada

Nakashiki, Norikazu; CRIEPI, Tokyo, Japan

Nishinomiya, Shaw; CRIEPI, Tokyo, Japan

Oh, Hee-Seok; University of Bristol, United Kingdom

Rahmstorf, Stefan; Potsdam Institute for Climate Impact Research, Germany

Rotstayn, Leon; Commonwealth Scientific and Industrial Research Organisation, Australia

Selten, Frank; Royal Netherlands Meteorological

Institute, The Netherlands

Short, Walter; National Renewable Energy Laboratory

Shuang, Zheng; Energy Research Institute, State Planning Development Council, PRC

Stocker, Thomas; Physics Institute, University of Bern, Germany

Thorpe, Alan J.; Meteorological Office, United Kingdom

Tzeng, Ren-Yow; National Central University, Taiwan

van Nispen tot Sevenaer, Cleo; Kluwer Academic Publishers

Verver, Ge; KNMI, The Netherlands

Visser, Hans; Power Generation and Sustainable Technology Department, KEMA, The Netherlands

Wainer, Ilana; Universidade de Sao Paulo, Brazil

Whitcher, Brandon; Eurandom, The Netherlands

Wood, Richard; Hadley Centre, United Kingdom

Yoshida, Yoshikatsu; CRIEPI, Tokyo, Japan

V. EDUCATION, TRAINING, AND KNOWLEDGE TRANSFER

The CGD objective in education, training, and knowledge transfer is to promote the advancement of science in general and of atmospheric science in particular, with an emphasis on climate research. Our target audience includes universities, other scientists, the public, and primary and secondary schools.

CGD utilizes a wide range of methods to meet our objective, from giving talks to elementary school classes to presenting invited talks at international scientific meetings. Our primary vehicle for transferring our advances in climate research is through the publication of our findings in scientific journals. In FY 98, FY 99, FY 00 we produced 106, 112, and 107 refereed publications, respectively. In FY00, eighty-eight (88) of the publications were co-authored. Appendix A lists CGD's publications for the past three fiscal years and this year.

A. Scholastic Interactions

CGD actively pursues its interactions with the scholastic community, and we plan to continue our strong participation in these areas. For the past three years as shown in Table 1, CGD staff members have given over 900 scientific and technical seminars, and over 60 non-technical presentations to the community. Annually, on average, our programs support about 14 postdoctoral candidates, three graduate students and four undergraduate students. Concurrently, our staff interacts with the university community by holding a variety of teaching appointments, acting as graduate advisors, and being members of thesis committees. For the past three years we have averaged 17 teaching appointments, advised 15 graduate students, and participated in 26 thesis committees. Table 2 shows CGD's university positions over the past three years.

B. Workshops

CGD has held several workshops over the past three years. These include three CCSM workshops, co-hosted an ASP Summer Colloquium, five ACACIA workshops, an adjunct applications workshop, an IPCC workshop, a VEMAP workshop, and 6 training sessions for users of our new NCL data processing tool. CGD and ASP (Advanced Study Program) hosted a summer colloquium in July 2000 at NCAR on "Dynamics of Decadal to Centennial Climate Variability." C. Deser and R. Saravanan (CGD) coordinated the sessions. The main goal of the colloquium was to acquaint graduate students and postdoctoral researchers with the current state of research on the subject of climate variability on time scales ranging from several years to several centuries. The focus was on the large-scale dynamics of the atmosphere and the oceans, with additional lectures on sea ice, land surface processes and biogeochemical and social aspects. ASP has started production of a written volume of the lectures presented by 25 people from 12 institutions of the U.S., Canada, France, and England. The 47 student participants represented 30 institutions from 10 foreign countries and the U.S. and were twice as many students as ASP usually supports.

The CCSM Workshop annually brings together many CCSM participants from NCAR, the universities, and other national laboratories. Each year, the number of attendees has increased. Over the past three years, we have averaged 197 participants, 64 NCAR and 133 non-NCAR. The purpose of the meeting is to discuss progress to date of each of the model components, the flux coupler and the science results from utilizing the coupled model. Equally important are the discussions regarding future plans for the components and future areas of research to investigate. Convening this workshop allows users and developers to interact and highlight successes and note where improvements are needed.

Along with participating at the CCSM workshop, the CCSM Working Groups usually meet once or twice more per year. These meetings are forums for information exchange and reaching consensus on recommendations for changes in the model or about allocations for computer time for major experiments. These working groups consist of scientists who come together to work on topics on which they share common interest. The groups are inclusive. The working groups allow scientists to participate in cooperative research to minimize unnecessary duplication and competition, so that improvements to CCSM can be made and so that high-quality uses of the CCSM can be achieved.

C. Outreach Training

The need for CCSM users to access, process, and visualize both model and observational data is recognized. Several CGD staff and members of NCAR's Scientific Computing Division have been developing and supporting software based upon the NCAR Command Language (NCL). CCSM users are trained on supported data processing and visualization tools through a web based e-knowledge portal and through three-day lecture/laboratory workshops.

The e-knowledge portal (Community Climate System Model Support Network http://www.cgd.ucar.edu/csm/support) contains three levels of knowledge content: context sensitive job assistance, structured training and user community information. Sensitive job assistance is defined to be hot-topic, immediate solution information that allows a user to overcome a productivity hurdle without having to wade through extraneous information. An example of this type of information is the graphical resource index (http://www.cgd.ucar.edu/csm/support/CSM_Graphics/advplot_index.shtml). This web page received 361 hits in January 2001. User community information is provided through two mailing lists, while structured learning is provided through a series of Power Point lectures, user's manuals, and over 200 example pages.

The "Data Processing and Visualization Workshops" feature the NCL, the netCDF operators and the Climate Model Processing Suite. These free, public domain, portable software packages are supported by CCSM and NCAR's SCD. The workshops cover the netCDF file format, NCL language basics, NCL file I/O (input/output), data processing, graphics, and file handling. Students listen to lectures and work through personalized problems in laboratory sessions. A total of sixty-seven students have attended an NCL Workshop (Table 3). These students consist of NCAR employees and university faculty and students. The universities represented include Yale, University of Utah, Purdue, UCLA, Harvard, University of Maine, University of North Carolina, University of California at Santa Cruz, and the University of Wisconsin. Two of the workshops were held off-site, one at UCLA, and the other at the University of California at Santa Cruz. Our program also provides staff liaisons to the CCSM. The purpose of these positions is to provide answers to questions raised by CCSM users, particularly those participating in working groups The support is provided remote scientists and local visitors. This outreach service provides support in areas of model characteristics, performance raw data output and post processing of the output. These liaison folk also are responsive to requests for data sets.

Table 1. Summary of CGD Educational Activities

	1998	1999	2000	Total	Average
Staff Appointments
Post Docs	10	10	23	43	14
GRAs	1	5	3	9	3
Undergrads	5	4	2	11	4
SOARS Students	3	3	0	6	2
Teaching
Appointments	17	15	19	51	17
Advisers	14	13	17	44	15
Members of Thesis Committee	26	26	25	77	26
Workshops	4	5	4	13	4
Seminars
Scientific	338	260	310	908	303
Non-technical	19	17	32	68	23
Total Seminars	357	277	342	976	325

Table 3. NCL Workshop Statistics

Dates	Location	Attending	NCAR	Univ
07-11 Feb 2000	NCAR	11	0	11
13-16 Nov 2000	NCAR	9	9	0
03-05 Jan 2001	UCLA	18	0	18
13-15 Feb 2001	UCSC	5	0	5
03-05 Apr 2001	NCAR	11	9	2
15-17 May 2001	NCAR	12	11	1

Table 2. CGD University Positions
Name of Staff Member	Teaching Appointments	Name of Institution	FY
Bonan, Gordon	Adjunct Professor	University of Colorado, Boulder	99, 00
Branstator, Grant	Collaborative Professor	Iowa State University	98, 99
Bryan, Frank	Resident Faculty & Lecturer	WOCE Young Investigators Workshop	00
Collins, William	Adjunct Member	Scripps Institution of Oceanography, University of California, San Diego	98
Deser, Clara	Faculty Affiliate	Colorado State University	98, 99
Doney, Scott	Adjunct Professor	University of Colorado, Boulder	98, 99
Errico, Ronald	Adjunct Professor	University of Utah	98
Hecht, Matthew	Visiting Professor	Colorado College	00
Holland, Marika	Guest Lecturer	University of Colorado, Boulder	98, 99
Hurrell, James	Graduate School Member	Purdue University	98, 99
Hurrell, James	Graduate School Member	University of Alabama at Huntsville	98, 99
Kasahara, Akira	Adjunct Professor	University of Utah	98, 99
Kiehl, Jeffrey	Adjunct Professor	University of Colorado, Boulder	98
Kittel, Timothy	Guest Lecturer	University of Colorado, Boulder	00
Kittel, Timothy	Instructor	Columbia University, New York	00
Lima, Ivan	Guest Lecturer	Peruvian Marine Institute (Lima, Peru)	00
McWilliams, James	Slichter Prof. of Earth Sciences	University of California, Los Angeles	98, 99
Rasch, Philip	Lecturer	University of Stockholm	98
Schimel, David	Adjunct Professor	University of Colorado, Boulder	98, 99
Schimel, David	Advising Professor	Colorado State University	98, 99
Seth, Anji	Adjunct Professor	University of Colorado, Boulder	98
Trenberth, Kevin	Graduate School Member	University of Colorado, Boulder	98, 99
Trenberth, Kevin	Lecturer	University of Colorado, Boulder	98, 99
Tribbia, Joe	Adjunct Professor	Iowa State University	99
Wilby, Robert L.	Senior Lecturer	University of Derby, United Kingdom	99

VI. IMPACT OF CENTER FUNDING

NCAR was established in 1960 to serve the broad university community as a "center" for research on atmospheric and related science problems, and is recognized for its scientific contributions to our understanding of the Sun-Earth system, including climate change, changes in atmospheric composition, solar physics and solar-terrestrial interactions, weather formation and forecasting, and the impacts of these complex and variable systems on human societies and vice versa. As an NSF funded center, NCAR has benefited from a 40-year history of stable support which has allowed it to serve the university community - and society at large - through the development, maintenance and provision of computational and observational facilities, advanced instrumentation, large-scope community models, logistical support efforts for community field campaigns, cutting-edge information technologies, and high-performance data archival and data curation systems. It also continues a tradition of excellence in broadly-based, collaborative and interdisciplinary scientific innovation across a full spectrum of geoscience disciplines.

As a physical center located in Boulder, Colorado, NCAR provides a unique setting where researchers from around the globe and across a wide spectrum of sciences can visit, collaborate, and interact. The center houses a broad array of tools and resources that are maintained by a world-class staff that functions within an effective university-based governance mechanism which ensures that the center can both lead - and be responsive to - the scientific agenda of the overall research community. The center provides a rich training ground for early-career scientists. It also serves as a stimulating locale for sabbaticals and visits from university and research-institute collaborators, benefiting all participants. As a national center, NCAR fulfills an important leadership role for the geosciences in helping to determine the shape and direction of both national and international research programs and initiatives. It also brings resources and capabilities to the national educational agenda through participating in a rich set of activities, including informal science education, K-12 educational module development, teacher workshops, undergraduate and professional training programs, and graduate and postdoctoral opportunities.

With the tremendous advances in information technologies, NCAR has also become more of a "virtual center", providing interactive access to data, information and knowledge on an unprecedented level. The future holds great promise as these capabilities expand, allowing NCAR to integrate expertise, knowledge, and technologies and making them available to the widest possible audience of scientists, collaborators, educators and the general public.

Providing a central locale and funding source has advantages in many of the research areas of CGD. A good example of this is the development of the CCSM. Having centralized funds to support a broad scientific climate research base has allowed for the multiple model component development of the CCSM. As previously described, the CCSM includes multiple components of the climate system. Scientists, specializing in the components of the atmospheric model, can develop the convection and radiation schemes while other scientists can focus on the ocean model. The model components are being expanded to include biogeochemistry, atmospheric chemicals, and upper atmosphere. This requires increased cross-divisional interactions with ACD, MMM, and the High Altitude Observatory (HAO). Having this expertise in-house increases the efficiency of the CCSM development. Coupling of atmosphere, land, ocean, and sea-ice model components needs multiple disciplines working closely together on a continual basis. Centralized funding and workspace facilitates this. Comparison of preliminary model output to data was shared among team members, which allowed for a variety of expertise to determine the plausible causes of biases and to plan corrective actions. Dedicated support staff provided concentrated times of development, testing, analyses and verification.

Another positive result of centralized funds is the ability to create a strong, viable visitor program. Collaborations with universities in the development, use, and analyses of the CCSM allow NCAR to focus on certain areas of climate problems or on the model’s improvement utilizing expertise that may not be available at NCAR. As described in Section V, we have convened workshops to discuss the uses of CCSM; base funding will permit us to conduct similar CCSM workshops. It will also allow the perpetuation of support for both graduate and post doctoral students.

Another advantage in center synergism for model development is the proximity of the computer resources and, in particular, a new dedicated CSL. Model designers can influence computer configuration and environment to ensure the model’s compatibility with development. Also developed with SCD has been the CCSM data processing and visualization tools. These tools have been developed quickly through interactions among the designers and developers in CGD and SCD and the end users. Centralized funding allows the contributors to be within close proximity to facilitate this development.

Conducting model development at a center allows us to undertake “higher-risk” science. With NSF funding provided annually with some assuredness, we are able to develop such a model as the CCSM. The coupling of the climate component models via a flux coupler was unique and untried. Many person-years of effort have already gone into the model development over the past several years, with final testing and analyses still months away. Having some fiscal security has allowed the CCSM to develop at a proper pace. Center support also creates leadership in this area because the ability of participants to focus on a common goal enhances synergism.

VII. FINANCIAL INFORMATION
CLIMATE AND GLOBAL DYNAMICS DIVISION
	FY 1998	FY 1999	FY 2000
NSF BASE FUNDS
Division Budget	5,685,700	6,284,100	6,413,600
Special Allocations from NCAR Directorate for*
Climate System Model (CSM) data mgmt.	45,000	-	-
Global Biogeochemistry	-	120,000	19,100
Ext. Middle Atmos. Comm. Climate Model (CCM)	-	96,200	-
Whole Atmos. Comm. Climate Model (WACCM)	-	-	112,600
Kasahara symposium	3,700	-	-
Support Scientist II position	5,000	-	-
Biogeochemistry Workshop	-	1,000
Support Scientist I position	-		20,300
Senior Scientist allocation	54,300	-	-
Global Tropos. Chemistry Program (GTCP)	-	20,000	-
US Weather Research Program (USWRP)	22,300	70,000	59,800
Allocations from NCAR Directorate /1	130,300	307,200	211,800
TOTAL NSF BASE FUNDS	5,816,000	6,591,300	6,625,400
NSF SPECIAL FUNDS/2	1,321,400	1,297,700	990,700
NON-NSF FUNDS/2	4,443,900	4,066,100	4,327,500
TOTAL	11,581,300	11,955,100	11,943,600
All figures include indirect costs at a rate of 45.7% to 46.9%, varying by year.
/1 One-time additional funding for divisions for equipment acquisition, visitors,
workshops, symposia, transitional funding for scientific appointments, etc.
Includes seed money and start-up funds for new initiatives. Also includes US
Weather Research Program (USWRP) and Global Tropospheric Chemistry
Program (GTCP) funds for science projects.
/2 The figures are actual spending for FY 1998 - FY 2000. NSF Special
includes Grantees.

VIII. APPENDICES

A. Publication List (1998 - 2001)

(*denotes most significant)

Achatz, U., and G. W. Branstator, 1999: A two-layer model with empirical linear corrections and reduced order for studies of internal climate variability, J. Atmos. Sci., 56, 3140-3160.

Albritton D., G. Meira Filho, U. Cubasch, X. Dai, Y. Ding, D. Griggs, B. Hewitson, J. Houghton, I. Isaksen, T. Karl, M. McFarland, V. P. Meleshko, J. Mitchell, M. Noguer, B. Nyenzi, M. Oppenheimer, J. Penner, S. Pollonais, T. Stocker, and K. Trenberth, 2001: Technical Summary. Climate Change 2001. The Science of Climate Change. Contribution of WG 1 to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J. T. Houghton, et al. (eds). Cambridge University Press, submitted.

Alexander, M., C. Deser, and M. Timlin, 1998: The re-emergence of SST anomalies in the North Pacific Ocean. J. Climate, 12, 2419-2431.

Alexander, M. A., J. D. Scott, and C. Deser, 2000: Processes that influence sea surface temperature and ocean mixed layer variability depth in a coupled model. J. Geophys. Res., 105, 16823-16842.

Asner, G. P., C. A. Wessman, and D. S. Schimel, 1998: Heterogeneity of savanna canopy structure and function from imaging spectrometry and inverse modeling. Ecological Applications 8, 1022-1036.

Asner, G. P., C. A. Wessman, D. S. Schimel, and S. Archer, 1998(a): Variability in leaf and litter optical properties: Implications for BRDF model inversions using AVHRR, MODIS, and MISR. Remote Sensing of Environment, 63, 243-257.

Asner, G. P., B. H. Braswell, D. S. Schimel, and C. A. Wessman, 1998(b): Ecological research needs from multiangle remote sensing data. Remote Sensing of Environment, 63, 155-165.

Asner, G. P., C. A. Wessman, and D. S. Schimel, 1998: Heterogeneity of savanna canopy structure and function from imaging spectrometry and inverse modeling. Ecological Applications, 8, 1022-1036.

Baird, A. J., and R. L. Wilby, Eds., 1999: Eco-Hydrology: Plants and Water in Terrestrial and Aquatic Environments. Routledge, 402 pp.

Barnett, T. P., D. W. Pierce, R. Saravanan, N. Schneider, D. Dommenget, M. Latif, 1999: Origins of the midlatitude Pacific decadal variability. Geophys. Res. Lett., 26, 1453-1456.

Barnett, T. P., D. W. Pierce, M. Latif, D. Dommenget, and R. Saravanan, 1999: Interdecadal interactions between the tropics and midlatitudes in the Pacific basin. Geophysical Research Letters, 26, 615-618.

Baron, J. S., M. D. Hartman, T. G. F. Kittel, L. E. Band, D. S. Ojima, R. B. Lammers, 1998: Effects of land cover, water redistribution, and temperature on ecosystem processes in the South Platte Basin. Ecological Applications, 8, 1037-1051.

Barth, M. C., P. J. Rasch, J. T. Kiehl, C. M. Benkovitz, and S. E. Schwartz, 2000: Sulfur chemistry in the National Center for Atmospheric Research Community Climate Model: Description, evaluation, features, and sensitivity to aqueous chemistry. J. Geophys. Res., 105, 1387-1415.

Berliner, L. M., J. A. Royle, C. K. Wikle, and R. F. Milliff, 1998: Bayesian methods in the atmospheric sciences. Bayesian Statistics 6, J. M. Barnardo, J. O. Berger, A. P. Dawid, and A. F. Smith, Eds., Oxford University Press, 83-100.

Berloff, P. S., and J. C. McWilliams, 1998: Large-scale, low-frequency variability in wind-driven ocean gyres. J. Phys. Oceanogr., 29, 1925-1949.

Berloff, P. S., and J. C. McWilliams, 1999: Quasigeostrophic dynamics of the western boundary current. J. Phys. Oceanogr., 29, 2607-2634.

Bitz, C. M., M. M., Holland, A. J. Weaver, and M. Eby, 2001: Simulating the ice-thickness distribution in a coupled climate model. Journal of Geophysical Research, 106, 2441–2463.

Bonan, G. B., 1998: The land surface climatology of the NCAR Land Surface Model coupled to the NCAR Community Climate Model. J. Climate, 11, 1307-1326.

Bonan, G. B., and L. M. Stillwell-Soller, 1998: Soil water and the persistence of floods and droughts in the Mississippi River Basin. Water Resour. Res., 34, 2693-2701.

Bonan, G. B., S. Levis, L. Kergoat, and K. Oleson, 2001: Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models. Global Biogeochemical Cycles, accepted for publication.

Bony, S., W. D. Collins, and D. W. Fillmore, 2000: Indian Ocean low clouds during the winter monsoon. J. Climate, 13, 2028-2043.

Boville, B. A., and J. W. Hurrell, 1998: A comparison of the atmospheric circulations simulated by the CCM3 and CSM1. J. Climate, 11, 1327-1341.

Boville, B. A., and P. R. Gent, 1998: The NCAR Climate System Model, Version One. J. Climate, 11, 1115-1130.

Boville, B. A., J. T. Kiehl, P. J. Rasch, and F. O. Bryan, 2001: Improvements to the NCAR CSM-1 for transient climate simulations. Journal of Climate, 14, 164-179.

Boyd, P., and S. C. Doney, 2000: The impact of climate change and feedback processes on the ocean carbon cycle. JGOFS Bergen Symposium Volume, Cambridge University Press, submitted.

Brady, E. C., R. M. DeConto, and S. L. Thompson, 1998: Deep water formation and poleward ocean heat transport in the warm climate extreme of the Cretaceous (80 Ma). Geophys. Res. Lett., 25:22, 4205-4208.

Bracco, A., J. C. McWilliams, G. Murante, A. Provenzale, and J. B. Weiss, 2001: Revisiting two-dimensional turbulence at modern resolution. Phys. Fluids A., accepted for publication.

Branstator, G., and S. E. Haupt, 1998: An empirical model of barotropic atmospheric dynamics and its response to tropical forcing. J. Climate, 11, 2645-2667.

Brasseur, G. P., J. T. Kiehl, J. -F. Muller, T. Schneider, C. Granier, X X Tie, and D. Hauglustaine, 1998: Past and future changes in global tropospheric ozone: Impact on radiative forcing. Geophys. Res. Lett., 25, 3807-3810.

Briegleb, B. P., and D. H. Bromwich, 1998: Polar radiation budgets of the NCAR CCM3. J. Climate, 11, 1246-1269.

Briegleb, B. P., and D. H. Bromwich, 1998: Polar climate simulation of the NCAR CCM3. J. Climate, 11, 1270-1286.

Bryan, F. O., 1998: Climate drift in a multicentury integration of the NCAR Climate System Model. J. Climate, 11, 1455-1471.

Celaya, M., J. Wahr, and F.O. Bryan, 1999: Climate driven polar motion. J. Geophys. Res., 104, 12 813-12 829.

Chang, P., R. Saravanan, L. Ji, and G. C. Hegerl, 2000: The effect of local sea-surface temperatures on atmospheric circulation over the tropical Atlantic sector. J. Climate, 13, 2195-2216.

Chao, Y., X. - J. Li, M. Ghil, and J. C. McWilliams, 2000: Pacific interdecadal variability in this century's sea surface temperatures. Geophys. Res. Lett., 27, 2261-2264.

Chase, T. N., R. A. Pielke, Sr., T. G. F. Kittel, J. S. Baron, and T. J. Stohlgren, 1999: Potential impacts on Colorado Rocky Mountain weather due to land use changes on the adjacent Great Plains. Journal of Geophysical Research, 104, 16673-16690.

Chase, T. N., R. A. Pielke, Sr., T. G. F. Kittel, R. R. Nemani, and S. W. Running, 1999: Simulated impacts of historical land cover changes on global climate in northern winter. Climate Dyn., 16, 93-105.

Chase, T. N., R. Pielke, Sr., T. G. F. Kittel, J. S. Baron, and T. J. Stohlgren, 1999: Impacts on Colorado Rocky Mountain weather due to land use changes on the adjacent Great Plains. J. Geophys. Res., 104, 16673-16690.

Chase, T. N., R. A. Pielke Sr., J. Knaff, T. G. F. Kittel, and J. Eastman, 2000: A comparison of regional trends in 1979-1997 depth-averaged tropospheric temperatures. Int. J. Climatology, 20, 503-518.

Chin, T. M., R. F. Milliff, and W. G. Large, 1998: Basin-scale, high-wavenumber sea surface wind fields from a multiresolution analysis of scatterometer data. J. Atmos. Ocean. Tech., 15, 741-763.

Ciais, P., P. Friedlingstein, D. S. Schimel, and P. P. Tans, 1999: A global calculation of the d¹³C of soil respired carbon: Implications for the biospheric uptake of anthropogenic CO2. Global Biogeochem. Cycles, 13, 519-530.

Clarke, A., W. D. Collins, P J. Rasch, V. Kapustin, K. Moore, and S. Howell, 2001: Pollution transport on global scales: Measurements and model predictions. Journal of Geophysical Research, accepted for publication.

Cleveland, C. C., A. R. Townsend, D. S. Schimel, H. Fisher, R. W. Howarth, L. O. Hedin, S. S. Perakis, E. F. Latty, J. C. Von Fischer, A. Elseroad, and M. F. Wasson, 1999: Global patterns of terrestrial biological nitrogen (N2) fixation in natural ecosystems. Global Biogeochem. Cycles, 13, 623-645.

Collins, W. D., 1998: A global signature of enhanced shortwave absorption by clouds. J. Geophys. Res. 103, 31 669-31 679.

Collins, W. D., A. Bucholtz, D. Lubin, P. Flatau, F. P. J. Valero, C. P. Weaver, and P. Pilewskie, 2000: Determination of surface heating by convective cloud systems in the central equatorial Pacific from surface and satellite measurements. Journal of Geophysical Research,. 105, 14807--14821.

*Collins, W. D., 2000: Effects of enhanced shortwave absorption on coupled simulations of the tropical climate system. Journal of Climate, 14, 1147--1165.

Collins, W. D., 2000: Parameterization of generalized cloud overlap for radiative calculations in general circulation models. Journal of Atmospheric Science, accepted for publication.

Collins, W. D., P .J. Rasch, B. E. Eaton, B. V. Khattatov, J. -F. Lamarque, and C. S. Zender, 2001: Simulating aerosols using a chemical transport model with assimilation of satellite aerosol retrievals: Methodology for INDOEX. Journal of Geophysical Research, accepted for publication.

Colucci, S. J., and D. P. Baumhefner, 1998: Numerical prediction of the onset of blocking: A case study with forecast ensembles. Mon. Wea. Rev., 126, 773-784.

Colucci, S. J., D. P. Baumhefner, and C. E. Konrad II, 1999: Numerical prediction of a cold-air outbreak: A case study with ensemble forecasts. Mon. Wea. Rev., 127, 1538-1550.

Constable, J. V. H., A. B. Guenther, D. S. Schimel, and R. K. Munson, 1999: Modeling changes in VOC emissions in response to climate change in the United States. Global Change Biology, 5, 791-806.

Covey, C., A. Abe-Ouchi, G. J. Boer, G. M. Flato, B. A. Boville, G. A. Meehl, U. Cubasch, E. Roeckner, H. Gordon, E. Guilyardi, L. Terray, X. Jiang, R. Miller, G. Russell, T. C. Johns, H. Le Treut, L. Fairhead, G. Madec, A. Noda, S. B. Power, E. K. Schneider, R. J. Stouffer, and J. -S. von Storch, 2000: The seasonal cycle in coupled ocean-atmosphere general circulation models. Climate Dyn., 16, 775-787.

Craig, S. G., K. J. Holmén, G. B. Bonan, and P. J. Rasch, 1998: Atmospheric CO₂ simulated by the National Center for Atmospheric Research Community Climate Model 1. Mean fields and seasonal cycles. J. Geophys. Res., 103, 13 213-13 235.

Cressie, N., and C. K. Wikle, 1998: The variance-based cross-variogram: You can add apples and oranges. Mathematical Geology, 30, 789-799.

Cubasch, U., G. A. Meehl, G. J. Boer, R. J. Stouffer, M. Dix, A. Noda, C. A. Senior, S. Raper and K. S. Yap, 2001: Projections of future climate change. Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J. T. Houghton, et al. Eds. Cambridge University Press, accepted for publication.

Dai, A., K. E. Trenberth, and T. R. Karl, 1998: Global variations in droughts and wet spells: 1900-1995. Geophys. Res. Lett., 25, 3367-3370.

Dai, A., 1999: Recent changes in the diurnal cycle of precipitation over the United States. Geophys. Res. Lett., 26, 341–344.

Dai, A., K. E. Trenberth and T. R. Karl, 1999: Effects of clouds, soil moisture, precipitation and water vapor on diurnal temperature range. J. Climate, 12, 2451–2473.

Dai, A., F. Giorgi, and K. E. Trenberth, 1999: Observed and model simulated precipitation diurnal cycles over the contiguous United States. J. Geophys. Res., 104, 6377-6402.

Dai, A., and J. Wang, 1999: Diurnal and semidiurnal tides in global surface pressure fields. J. Atmos. Sci., 56, 3874-3891.

Dai, A., and T. M. L. Wigley, 2000: Global patterns of ENSO-induced precipitation. Geophys. Res. Lett., 27, 1283-1286.

Dai, A., and C. Deser, 1999: Diurnal and semidiurnal variations in global surface wind and divergence fields. J. Geophys. Res., 104, 31 109-31 125.

Dai, A., 2001: Global precipitation and thunderstorm frequencies. Part I: Seasonal and interannual variations. J. Climate, 14, 1092-1111.

Dai, A., 2001: Global precipitation and thunderstorm frequencies. Part II: Diurnal variations. J. Climate, 14, 1112-1128..

Dai, A., T. M. L. Wigley, B. A. Boville, J. T. Kiehl, and L. E. Buja, 2001: Climates of the 20th and 21st centuries simulated by the NCAR Climate System Model. Journal of Climate, 14, 485-519.

Dai, A., G. A. Meehl, W. M. Washington, T. M. L. Wigley, and J. M. Arblaster, 2001: Ensemble simulation of 21st century climate changes: business as usual vs. CO₂ stabilization. Bull. Amer. Meteor. Soc., accepted for publication.

Danabasoglu, G., 1998: On the wind-driven circulation of the uncoupled and coupled NCAR Climate System Ocean Model. J. Climate, 11, 1442-1454.

Danabasoglu, G., and J. C. McWilliams, 2000: An upper-ocean model for short-term climate variability. J. Climate, 13, 3380-3411.

Dawson, C. W., and R. L. Wilby, 1998: An artificial neural network approach to rainfall-runoff modelling. Hydrological Sciences Journal, 43, 47-66.

Dawson, C. W., M. Brown, and R. L. Wilby, 2000: Inductive learning approaches to rainfall–runoff modelling. International Journal of Neural Systems, 10, 43-57.

Dawson, C. W., and R. L. Wilby, 2000: A comparison of artificial neural networks used for rainfall-runoff modelling. Hydrology and Earth Systems Science, 3, 529-540.

Dawson, C. W., and R. L. Wilby, 2001: Hydrological modelling using artificial neural networks. Progress in Physical Geography, accepted for publication.

Deser, C., and C. A. Smith, 1998: Diurnal and semidiurnal variations of the surface wind field over the tropical Pacific Ocean. J. Climate, 11, 1730-1748

Deser, C., M. A. Alexander, and M. S. Timlin, 1999: Evidence for a wind-driven intensification of the Kuroshio Current Extension from the 1970s to the 1980s. J. Climate, 12, 1697-1706.

*Deser, C., J. E. Walsh, and M. S. Timlin, 1999: Arctic sea ice variability in the context of recent atmospheric circulation trends. J. Climate, 13, 617-633.

Deser, C., 2000: On the teleconnectivity of the "Arctic Oscillation." Geophys. Res. Lett., 27, 779-782.

Deser, C., M. A. Alexander, and M. S. Timlin, 2000: Reply to Drs. Latif and Ventzke comments on “Evidence for a wind-driven intensification of the Kuroshio Current Extension from the 1970s to the 1980s.” J. Climate, 13, 1995.

Dickey, T., S. Zedler, D. Frye, H. Jannasch, D. Manov, D. Sigurdson, J. D. McNeil, L. Dobeck, X. Yu, T. Gilboy, C. Bravo, S. C. Doney, D. A. Siegel, and N. Nelson, 2001: High temporal resolution measurements from the Bermuda testbed mooring: June 1994 - March 1998. Deep-Sea Res. II, accepted for publication.

Dickson, R. R., J. W. Hurrell, M. McCartney, H. L. Bryden, R. Williams, and J. Marshall, 1998: The North Atlantic Oscillation. Chapter 5 of CLIVAR Implementation Plan, WCRP No. 103, WMO/TD-No. 869, ICOP No. 14, 163-192.

Dickson, R. R., T. J. Osborn, J. W. Hurrell, J. Meincke, J. Blindheim, B. Adlandsvik, T. Vinje, G. Alekseev, and W. Maslowski, 2000: The Arctic Ocean response to the North Atlantic Oscillation. J. Climate, 13, 2671-2696.

Dickson, R. R., J. W. Hurrell, N. L. Bindoff, A. P. S. Wong, B. Arbic, B. Owens, S. Imawaki, and I. Yashayaev, 2001: The world during WOCE. Ocean Circulation and Climate, G. Siedler and J. Church, Eds., Academic Press, accepted for publication.

Doney, S. C., J. L. Bullister, and R. Wanninkhof, 1998: Climatic variability in upper ocean ventilation diagnosed using chlorofluorocarbons. Geophys. Res. Lett., 25, 1399-1402.

Doney, S. C., W. G. Large, and F. O. Bryan, 1998: Surface ocean fluxes and water-mass transformation rates in the coupled NCAR Climate System Model. J. Climate, 11, 1422-1443.

Doney, S. C., 1999: Major challenges confronting marine biogeochemical modeling. Global Biogeochem. Cycles, 13, 705-714.

Doney, S. C., D. W. R. Wallace, and H. W. Ducklow, 2000: The North Atlantic Carbon Cycle: New perspectives from JGOFS and WOCE. The Dynamic Ocean Carbon Cycle: A Midterm Synthesis of the Joint Global Ocean Flux Study, R. B. Hanson, H. W. Ducklow, and J. G. Field, Eds., Cambridge University Press, 373-391.

Doney, S. C., and D. M. Glover, 2001: Ocean process tracers: modelling the ocean carbon cycle. Encyclopedia of Ocean Sciences, J. Steele, Ed., Academic Press, accepted for publication.

Doney, S. C. and M. W. Hecht, 2001: Antarctic bottom water formation and deep water chlorofluorocarbon distributions in a global ocean climate model. Journal of Physical Oceanography, accepted for publication.

Doney, S. C., D. M. Glover, M. Fuentes, and S. McCue, 2001: Mesoscale variability of satellite ocean color: Global patterns and spatial scales. Journal of Geophysical Research, Oceans, submitted.

Douglass, A. R., M. P. Prather, T. Hall, S. E. Strahan, P. Rasch, L. Sparling, L. Coy, and J. M. Rodriquez: 1999, Choosing meteorological input for the global modeling initiaitve assessment of high speed aircraft, Journal of Geophysical Research, 104, 27545-27564.

Dutay, J. C., J. L. Bullister, S. C. Doney, J. C. Orr, R. Najjar, K. Caldeira, J. -M. Champin, H. Drange, M. Follows, Y. Gao, N. Gruber, M. W. Hecht, A. Ishida, F. Joos, K. Lindsay, G. Madec, E. Maier-Reimer, J. C. Marshall, R. J. Matear, P. Monfray, G. -K. Plattner, J. Sarmiento, R. Schlitzer, R. Slater, I. J. Totterdell, M. ‑F. Weirig, Y. Yamanaka, and A. Yool, 2001: Evaluation of ocean model ventilation with CFC-11: Comparison of 13 global ocean models. Ocean Modelling, accepted for publication.

Easterling, D. R., T. R. Karl, K. P. Gallo, D. A. Robinson, K. E. Trenberth, and A. Dai, 2000: Observed climate variability and change of relevance to the biosphere. J. Geophys. Res., 105, 20 101-20 114.

Easterling, D. R., G. A. Meehl, C. Parmesan, S. Changnon, T. R. Karl, and L. O. Mearns, 2000: Climate extremes: Observations, modeling and impacts. Science, 289, 2068-2074.

Ehrendorfer, M., R. M. Errico, and K. D. Raeder, 1999: Singular vector perturbation growth in a primitive equation model with moist physics. J. Atmos. Sci., 56, 1627-1648.

Errico, R. M., and K. D. Raeder, 1998: An examination of the accuracy of the linearization of a mesoscale model with moist physics. Quart. J. Roy. Meteor. Soc., 125, 169-195.

Errico, R. M., 1999: Workshop on assimilation of satellite data. Bull. Amer. Meteor. Soc., 80, 463-471.

Errico, R. M., 1999: Report of the workshop on assimilation of satellite data held at NASA/GSFC 21-23 April 1998. Bull Amer. Meteor. Soc., 80, 463-471.

Errico, R. M., 2000: Interpretations of the total energy and rotational energy norms applied to determination of singular vectors. Quart. J. Roy. Meteor. Soc., 126A, 1581-1599.

Errico, R. M., 2000: The dynamical balance of singular vectors in a primitive equation model. Quart. J. Roy. Meteor. Soc., 126A, 1601-1618.

Errico, R. M., 2000: On the lack of accountability in meteorological research. Bull. Amer. Meteor. Soc., 81, 1333-1337.

Errico, R. M., M. Ehrendorfer, and K. D. Raeder, 2001: The spectra of singular values in a regional model. Tellus, accepted for publication.

Errico, R. M., L. Fillion, D. Nychka, and Z. -Q. Lu, 2000: Some statistical considerations associated with the data assimilation of precipitation observations. Quart. J. Roy. Meteor. Soc., 126A, 339-359.

Errico, R. M., G. Ohring, J. Derber, and J. Joiner, 2000: NOAA/NASA/DoD workshop on satellite data assimilation. Bull. Amer. Meteor. Soc., 81, 2457-2462.

Eugster W., W. R. Rouse, R. A. Pielke, Sr., J. P. McFadden, D. D. Baldocchi, T. G. F. Kittel, F. S. Chapin, III, G. E. Liston, P. L. Vidale, E. Vaganov, and S. Chambers, 2000: Land-atmosphere energy exchange in arctic tundra and boreal forest: available data and feedbacks to climate. Global Change Biology, 6 (suppl 1):84-115.

Fournier, A., 1998: Transfers and fluxes of wind kinetic energy between orthogonal wavelet components during atmospheric blocking. Wavelets in Physics, J. C. van den Berg, Ed., Cambridge University Press, 263-298.

Fournier, A., 2001: Introduction to orthonormal wavelet analysis with shift invariance: Application to observed atmospheric-blocking spatial structure. J. Atmos. Sci., accepted for publication.

Fox, H. R., H. M Moore, and R. L. Wilby, 2001: The impact of river regulation and climate change on the barred estuary of the Oued Massa, southern Morocco. Regulated Rivers, accepted for publication.

Frederiksen, J. S., and G. Branstator, 2001: Seasonal and intraseasonal variability of large-scale barotropic modes. J. Atmos. Sci., accepted for publication.

Fuentes, M., 2000: Predicting integrals of diffusion processes with unknown diffusion parameters. Stochastics, 69, 255-283.

Fuentes, M., S. C. Doney, D. M. Glover, and S. J. McCue, 2000: Spatial structure of the SeaWiFS ocean color data for the North Atlantic Ocean. Statistics for Understanding the Atmosphere, M. Berliner, D. Nychka, and T. Hoar, Eds., Springer-Verlag, 153-171.

Fung, I. Y., S. K. Meyn, I. Tegen, S. C. Doney, J. G. John, and J. K. B. Bishop, 2000: Iron supply and demand in the upper ocean. Global Biogeochem. Cycles, 14, 281-295.

Garcon, V. C., A. Oschlies, S. C. Doney, D. McGillicuddy, and J. Waniek, 2001: The role of mesoscale variability on plankton dynamics. Deep-Sea Res. II, accepted for publication.

Gent, P. R., F. O. Bryan, G. Danabasoglu, S. C. Doney, W. R. Holland, W. G. Large, and J. C. McWilliams, 1998: The NCAR Climate System Model global ocean component. J. Climate, 11, 1287-1306.

Gent, P. R., W. G. Large, and F. O. Bryan, 2000: What sets the mean transport through Drake Passage? J. Geophys. Res., 106, 2693-2712.

Gent, P. R., 2000: Will the North Atlantic Ocean thermohaline circulation weaken during the 21st century? Geophys. Res. Lett., 106, 2693-2712.

Ghan, S., D. Randall, K. -M. Xu, R. Cederwall, D. Cripe, J. J. Hack, S. Iacobellis, S. Klein, S. Krueger, U. Lohmann, J. Pedretti, A. Robock, L. Rotstayn, R. Somerville, G. Stenchikov, Y. Sud, G. Walker, S. Xie, J. Yio, and M. Zhang, 2000: A comparison of single column model simulations of summertime midlatitude continental convection. J. Geophys. Res., 105, 2091-2124.

Giorgi, F., G. A. Meehl, A. Kattenberg, H. Grassl, J. F. B. Mitchell, R. J. Stouffer, T. Tokioka, A. J. Weaver, and T. M. L. Wigley, 1998: Simulation of regional climate change with global coupled climate models and regional modeling techniques. IPCC Special Report on the Regional Impacts of Climate Change: An Assessment of Vulnerability, R. T. Watson, M. C. Zinyowera, and R. H. Moss, Eds., Cambridge University Press, 427-437.

Grunwald, G. K., and R. H. Jones, 2000: Markov models for time series with mixed distribution. Environmetrics, 11, 327-339.

Hack, J. J., 1998: Analysis of the improvement in implied meridional ocean energy transport as simulated by the NCAR CCM3, J. Climate, 11, 1237-1244.

Hack, J. J., 1998: Sensitivity of the simulated climate to a diagnostic formulation for cloud liquid water. J. Climate, 11, 1497-1515.

Hack, J. J., J. T. Kiehl, and J. W. Hurrell, 1998: The hydrologic and thermodynamic characteristics of the NCAR CCM3. J. Climate, 11, 1179-1206.

Hack, J. J., and J. A. Pedretti, 2000: Assessment of solution uncertainties in single-column modeling frameworks. J. Climate, 13, 352-365.

Hamill, T. M., S. L. Mullen, C. Snyder, Z. Toth, and D. P. Baumhefner, 2000: Ensemble forecasting in the short to medium range: Report from a workshop. Bull. Amer. Meteor. Soc., 81, 2653-2664.

Hassan, H., A. Aramaki, K. Hanaki, T. Matsuo, and R. L. Wilby, 1999: Lake stratification and temperature profiles simulated used downscaled GCM output. Wat. Sci. Tech., 38, 217–226.

Hay, L. E., R. L. Wilby, and G. H. Leavesley, 2000: A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States. J. Amer. Water Resources Assoc., 36, 387-397.

Hecht, M. W., F. O. Bryan, and W. R. Holland, 1998: A consideration of tracer advection schemes in a primitive equation ocean model. J. Geophys. Res., 103, 3301-3321.

Hecht, M. W., B. A. Wingate, and P. Kassis, 2000: A better, more discriminating test problem for ocean tracer transport. Ocean Modelling, 2, 1-15.

Heymsfield, A. J., G. M. McFarquhar, W. D. Collins, J. A. Goldstein, F. P. J. Valero, J. Spinhirn, W. Hart, and P. Pilewskie, 1998: Cloud properties leading to highly reflective tropical cirrus: Interpretations from CEPEX, TOGA COARE, and Kwajalein, Marshall Islands. J. Geophys. Res., 103, 8805-8812.

*Hoerling, M. P., J. W. Hurrell, and T. Xu, 2001: Tropical origins for recent North Atlantic climate change. Science, accepted for publication.

Hoffert, M. I., A. K. Caldeira, A. K. Jain, E. F. Haites, L. D. D. Harvey, S. D. Potter, M. E. Schlesinger, S. H. Schneider, R. G. Watts, T. M. L. Wigley, and D. J. Wuebbles, 1999: Energy Implications of CO₂ Stabilization. Nature, 395, 881-884.

Holland, M. M., A. J. Brasket, and A. J. Weaver, 2000: The impact of rising atmospheric CO₂ levels on simulated sea ice induced thermohaline circulation variability, Geophys. Res. Lett., 10, 1519-1522.

Holland, M. M., C. M. Bitz, M. Eby, and A. J. Weaver, 2001: The role of ice-ocean interactions in the variability of the North Atlantic thermohaline circulation. J. Climate, accepted for publication.

Holland, M. M., 2000: The influence of ice/ocean coupling feedbacks on Arctic sea ice variability, Journal of Climate, submitted.

Holland, W. R., J. C. Chow, and F. O. Bryan, 1998: Application of a third-order upwind scheme in the NCAR Ocean Model. J. Climate, 11, 1487-1493.

Horinouchi, T., F. Sassi and B. A. Boville, 2000: Synoptic-scale Rossby waves and the geographic distribution of lateral transport routes between the tropics and the extratropics in the lower stratosphere. Journal of Geophysical Research, 105, 26579-26592.

Hua, B. L., J. C. McWilliams, and P. Klein, 1998: Lagrangian acceleration and dispersion in geostrophic turbulence. J. Fluid Mech., 366, 87-108.

Huber, M., M. Ghil, and J. C. McWilliams, 2001: A Lagrangian investigation of large-scale atmospheric turbulence. J. Atmos. Sci., accepted for publication.

Hulme, M., T. M. L. Wigley, E. M. Barrow, S. C. B. Raper, A. Centella, S. J. Smith, and A. C. Chipanshi, 2000: Using a climate scenario generator for vulnerability and adaptation assessments: MAGICC and SCENGEN Version 2.4 Workbook and CD-Rom, B. Lim and J. Smith, Eds. Climatic Research Unit, 52 pp.

Hurrell, J. W., 1998: Relationships among recent atmospheric circulation changes, global warming, and satellite temperatures. Science Progress, 81, 205-224.

*Hurrell, J. W., and K. E. Trenberth, 1998: Difficulties in obtaining reliable temperature trends: Reconciling the surface and satellite MSU records. J. Climate, 11, 945-967.

Hurrell, J. W., H. van Loon, and D. J. Shea, 1998: The mean state of the troposphere. Meteorology of the Southern Hemisphere, D. Karoly and D. Vincent, Eds., Amer. Meteor. Soc., 1-46.

Hurrell, J. W., J. J. Hack, B. A. Boville, D. L. Williamson, and J. T. Kiehl, 1998: The dynamical simulation of the NCAR Community Climate Model Version 3 (CCM3). J. Climate, 11, 1207-1236.

Hurrell, J. W., and K. E. Trenberth, 1999: Global sea surface temperature analyses: multiple problems and their implications for climate analysis, modeling, and reanalysis. Bull. Amer. Meteor. Soc., 80, 2661-2678.

Hurrell, J. W., S. J. Brown, K. E. Trenberth, and J. R. Christy, 2000: Comparison of tropospheric temperatures from radiosondes and satellites: 1979–98. Bull. Amer. Meteor. Soc., 81, 2165-2177.

Hurrell, J. W., 2001: Climate Variability: North Atlantic and Arctic Oscillation. Encyclopedia of Atmospheric Sciences, J. Holton, J. Pyle, and J. Curry, Eds., accepted for publication.

Hurrell, J. W., 2001: Climate: North Atlantic and Arctic Oscillation. Encyclopedia of Ocean Sciences, J. Steele, S. Thorpe, and K. Turekian, Eds., accepted for publication.

Hurrell, J. W., M. P. Hoerling, and C. K. Folland, 2001: Climatic variability over the North Atlantic. Meteorology at the Millenium: 150^th Anniversary of the Royal Meteorological Society, Academic Press, accepted for publication.

Hurrell, J. W., Y. Kushnir, and M. Visbeck, 2001: The North Atlantic Oscillation. Science, 291, 603-605.

Jayaraman, A., A. D. Lubin, S. Ramachandran, V. Ramanathan, E. Woodbridge, W. D. Collins, and K. S. Zalpuri, 1998: Direct observations of aerosol radiative forcing over the tropical Indian Ocean during the January-February 1996 pre-INDOEX cruise. J. Geophys. Res., 103, 13 827-13 836.

Joyce, T. M., C. Deser, and M. A. Spall, 2000: The relation between decadal variability of subtropical mode water and North Atlantic Oscillation. J. Climate, 13, 2550-2569.

Julien, K., J. Werne, S. Legg, and J. C. McWilliams, 2001: The effects of rotation on the global dynamics of turbulent convection. Solar Convection and Oscillations, J. Christensen-Dalsgaard and F. P. Pipjers, Eds., Kluwer Academic Publishers, accepted for publication.

Julien, K., S. Legg, J. C. McWilliams, and J. Werne, 1998: Plumes in rotating convection. Part 1: Ensemble statistics and dynamical balances. J. Fluid Mech., 391, 151-187.

Karl, T., and K. E. Trenberth, 1999: The human impact on climate. Sci. Amer., 281, 100-105.

Kasahara, A., and J. -H. Qian, 2000: Normal modes of a global nonhydrostatic atmospheric model. Mon. Wea. Rev., 128, 3357-3375.

Keeling, R. F., B. B. Stephens, R. G. Najjar, S. C. Doney, D. Archer, and M. Heimann, 1998: Seasonal variations in the atmospheric O₂/N₂ ratio in relation to the kinetics of air-sea gas exchange. Global Biogeochem. Cycles, 12, 141-163.

Kelly, R. H., W. J. Parton, M. D. Hartman, L. K. Stretch, D. S. Ojima, and D.S. Schimel, 2000: Intra-annual and interannual variability of ecosystem processes in shortgrass steppe. Journal of Geophysical Research, 105, 20,093-20,100.

Kiehl, J. T., 1998: Simulation of the tropical Pacific warm pool with the NCAR Climate System Model. J. Climate, 11, 1342-1355.

Kiehl, J. T., J. J. Hack, and J. W. Hurrell, 1998: The energy budget of the NCAR Community Climate Model: CCM3. J. Climate, 11, 1151-1178.

Kiehl, J. T., J. J. Hack, G. B. Bonan, B. B. Boville, D. L. Williamson, and P. J. Rasch, 1998: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate, 11, 1131-1149.

*Kiehl, J. T., T. L. Schneider, R. W. Portmann, and S. Solomon, 1999: Climate forcing due to tropospheric and stratospheric ozone. J. Geophys. Res., 104, 31 239-31 254.

Kiehl, J. T. T. L. Schneider, P.J. Rasch, M. Barth and J. Wong, 2000: Radiative Forcing due to Sulfate aerosols from simulations with the NCAR Community Climate Model (CCM3), Journal of Geophysical Research., 105, 1441-1457.

Kinney, R. M., and J. C. McWilliams, 1998: Turbulent cascades in anisotropic magnetohydrodynamics. Phys. Rev. E, 57, 7111-7121.

Kinney, R. M., and J. C. McWilliams, 1999: Reduced dynamical equations for the high-latitude thermosphere: Ion drag balance. Geophys. Res., 104, 6805-6812.

Kinney, R. M., B. Chandran, S. Cowley, and J. C. McWilliams, 2001: Magnetic field growth and saturation in plasmas with high Prandtl number. Part I: The two-dimensional case. Astrophys. J., accepted for publication.

Kinney, R. M., F. Coroniti, J. C. McWilliams, and P. Pritchett, 2001: Mechanisms for discrete auroral arc breakup by nonlinear Alfven wave interaction. J. Geophys. Res., accepted for publication.

Kinnison, D. E., P. S. Connell, J. M. Rodriguez, D. A. Rotman, D. B. Considine, J. Tannahill, R. Ramaroson, P. J. Rasch, A. R. Douglas, S. L. Baughcum, L. Coy, D. W. Waugh, S. R. Kawa, and M. J. Prather, 2001: The global modeling initiative assessment model: Application to high-speed civil transport perturbation. Journal of Geophysical Research, 106, 1693-1711.

Kittel, T. G. F., 1998: Effects of climatic variability on herbaceous phenology and observed species richness in temperate montane habitats, Lake Tahoe Basin, Nevada. Madrono, 45, 75-84.

Kittel, T., D. Schimel, N. Rosenbloom, and H. Fisher, 1998: U.S. climate and ecological data available on CD-ROM and online. Eos, 79, 47.

Kittel, T., D. Schimel, N. Rosenbloom, and H. Fisher, 1998: VEMAP U.S. climate, vegetation, and soils dataset available on CD ROM and on line. The Biogeographer, 55, 2.

Kittel, T. G. F., F. Giorgi, and G. A. Meehl, 1998: Intercomparison of regional biases and doubled CO₂ sensitivity of coupled atmosphere-ocean general circulation model experiments. Climate Dyn., 14, 1-15.

Kittel, T. G. F., W. L. Steffen, and F. S. Chapin, III, 2000: Global and regional modeling of arctic-boreal vegetation distribution and its sensitivity to altered forcing. Global Change Biology, 6 (suppl 1):1-18.

Kleypas, J. A., R. W. Buddemeier, and J. -P. Gattuso, 2001: The future of coral reefs in an age of global change. Int. J. Earth Sciences, accepted for publication.

Kleypas, J. A., R. W. Buddemeier, D. Archer, J.-P. Gattuso, C. Langdon, and B. N. Opdyke, 1999: Geochemical consequences of increased atmospheric CO₂ on coral reefs. Science, 284, 118-120.

Kleypas, J. A., J. McManus, and L. Menez, 1999: Using environmental data to define reef habitat: Where do we draw the line? Am. Zool., 39, 146-159.

Koshyk, J. N., B. A. Boville, K. Hamilton, E. Manzini, and K. Shibata, 1999: Kinetic energy spectrum of horizontal motions in middle-atmosphere models. J. Geophys. Res., 104, 27 177-27 190.

Labitzke, K. G., and H. van Loon, 1999: The Stratosphere Phenomena, History, and Relevance. Springer-Verlag, 179 pp.

Labitzke, K. G., and H. van Loon, 2000: The QBO effect on the solar signal in the global stratosphere in the winter of the Northern Hemisphere. J. Atmos. Solar-Terr. Phys., 62, 621-628.

Lal, M., G. A. Meehl, and J. M. Arblaster, 2001: Simulation of Indian summer monsoon rainfall and its intraseasonal variability. Regional Environmental Change, accepted for publication.

Large, W. G., and P. R. Gent, 1999: Validation of vertical mixing in an equatorial ocean model using large eddy simulations and observations. J. Phys. Oceanogr., 29, 449-464.

*Large, W. G., G. Danabasoglu, J. C. McWilliams, P. R. Gent, and F. O. Bryan, 2001: Equatorial circulation of a global ocean climate model with anisotropic horizontal viscosity. J. Phys. Oceanogr., 31, 518-536.

Lawrence, M. J, P. J. Crutzen, P. J. Rasch, B. E. Eaton, and N. M. Mahowald, 2000: A model for studies of tropospheric photochemistry: 1. Description and global simulation characteristics. Journal of Geophysical Research, accepted for publication.

Lee, K., R. Wanninkhof, T. Takahashi, S. C. Doney, and R. A. Feely, 1998: Low interannual variability in recent oceanic uptake of atmospheric carbon dioxide. Nature, 396, 155-159.

Lee, J. M., S. C. Doney, G. Brasseur, and J. -F. Muller, 1998: A global three-dimensional atmosphere-ocean model of methyl bromide distributions. J. Geophys. Res., 103, 16 039-16 059.

Legg, S., J. C. McWilliams, and J. Gao, 1998: Localization of deep ocean convection by a geostrophic eddy. J. Phys. Oceanogr., 48, 944-970.

Legg, S., and J. C. McWilliams, 1999: Temperature and salinity variability in heterogeneous oceanic convection. J. Phys. Oceanogr., 30, 1188-1206.

Legg, S., and J. C. McWilliams, 2001: Convective modifications of a geostrophic eddy field. J. Phys. Oceanogr., accepted for publication.

Lejenäs, H., and R. A. Madden, 2000: Mountain torques caused by normal-mode global Rossby Waves, and the impact on atmospheric angular momentum. J. Atmos. Sci., 57, 1045-1051.

Levine, R. A., and L. M. Berliner, 1999: Statistical principles for climate change studies. J. Climate, 12, 564-574.

Lewis, J., K. D. Raeder, and R. Errico, 2001: Vapor flux associated with return flow over the Gulf of Mexico: A sensitivity study using adjoint modeling. Tellus, accepted for publication.

Li, X., Y. Chao, J. C. McWilliams, and L. -L. Fu, 2001: A comparison of two vertical mixing schemes in a Pacific Ocean general circulation model. J. Climate, accepted for publication.

Lietzke, C. E., C. Deser, and T. H. Vonder Haar, 2001: Evolutionary structure of the eastern Pacific doubled ITCZ based on satellite moisture profile retrievals. J. Climate, accepted for publication.

Limpasuvan, V., C. B. Leovy, Y. J. Orsolini, and B. A. Boville, 2000: A numerical simulation of the two-day wave near the stratopause. J. Atmos. Sci., 57, 1702-1717.

Liu, S., W. A. Reiners, M. Keller, and D. S. Schimel, 1999: Model simulation of changes in N₂O and NO emissions with conversion of tropical rain forests to pastures in the Costa Rican Atlantic Zone. Global Biogeochem. Cycles, 13, 663-677.

Liu, S., W. A. Reiners, M. Keller, and D. S. Schimel, 2000: Simulation of nitrous oxide and nitric oxide emissions from tropical primary forests in the Costa Rican Atlantic Zone. Environmental Modeling and Software, 15, 727-743.

Lu, Z-Q. and L. M. Berliner, 1999: Markov switching time series models with application to daily runoff series. Water Resour. Res., 35, 523–534.

Lohmann,U., W. R. Leaitch, K. Law, L. Barrie, Y. Yi, D. Bergmann, C. Bridgeman, M. Chin, J. Christensen, R. Easter, J. Feichter, A. Jeuken, E. Kjellstrom, D. Koch, C. Land, P. Rasch and G.-J. Roelofs, 1999: Vertical distributions of sulfur species simulated by large scale atmospheric mo dels in COSAM: Comparison with observations, Tellus, accepted for publication..

Lomax, B. H., D. J. Beerling, G. R. Upchurch, Jr., and B. L. Otto-Bliesner, 2000: Terrestrial ecosystem responses to global environmental change across the Cretaceous-Tertiary boundary. Geophys. Res. Lett., 27, 2149-2152.

Madden, R. A., T. J. Hoar, and R. F. Milliff, 1998: Scatterometer winds composited according to the phase of the Tropical Intraseasonal Oscillation. Tellus, 51A, 263-272.

Madden, R. A., D. J. Shea, R. W. Katz, and J. W. Kidson, 1998: The potential for long-range predictability of precipitation over New Zealand. Int. J. Climate, 19. 405-421.

Madden, R. A., H. Lejenäs, and J. J. Hack, 1998: Semi-diurnal variations in the budget of angular momentum in a general circulation model and in the real atmosphere. J. Atmos. Sci., 55, 2561-2575.

Madden, R. A., and D. J. Shea, 1999: The potential for long-range predictability of temperature and precipitation over Japan. J. Meteor. Soc. Japan, 77, 1111-1121.

Magnusdottir, G., and R. Saravanan, 2000: The response of atmospheric heat transport to zonally averaged SST trends. Tellus, 51A, 815-832.

Marchesiello, P., J. C. McWilliams, and A. Shchepetkin, 2001: Open boundary conditions for long-term integration of regional ocean Taimodels. Ocean Modelling, accepted for publication.

Marshall, J., F. Dobson, K. Moore, P. Rhines, M. Visbeck, E. d’Asaro, K. Bumke, S. Chang, R. Davis, K. Fischer, R. Garwood, P. Guest, R. Harcourt, C. Herbaut, T. Holt, J. Lazier, S. Legg, J. C. McWilliams, R. Pickart, M. Prater, I. Renfrew, F. Schott, U. Send, and W. Smethie, 1998: The Labrador Sea deep convection experiment. Bull. Amer. Meteor. Soc., 79, 2033-2058.

Marshall, J., Y. Kushnir, D. Battisti, P. Chang, J. W. Hurrell, M. McCartney, and M. Visbeck, 2001. Atlantic climate variability: observations and mechanisms. International Journal of Climatology, accepted for publication.

McFarquhar, G. M., A. J. Heymsfield, A. Macke, J. Iaquinta, and S.M. Aulenbach, 1999: Use of observed ice crystal sizes and shapes to calculate mean scattering properties and multi-spectral radiances: CEPEX 4 April 1993 case study. J. Geophys. Res., 104, 31,763-31,779.

McWilliams, J. C., and I. Yavneh, 1998: Fluctuation growth and instability associated with a singularity of the balance equations. Physics of Fluids, 10, 2587-2596

McWilliams, J. C., I. Yavneh, M. J. P. Cullen, and P. R. Gent, 1998: The breakdown of large-scale flows in rotating, stratified fluids. Physics of Fluids, 10, 3178-3184.

McWilliams, J. C., and J. M. Restrepo, 1999: The wave-driven ocean circulation. J. Phys. Oceanogr., 29, 2523-2540.

McWilliams, J. C., J. B. Weiss, and I. Yavneh, 1999: The vortices of homogeneous geostrophic turbulence. J. Fluid Mech., 401, 1-26.

McWilliams, J. C., I. Yavneh, M. J. P. Cullen, and P. R. Gent, 1999: Limits of balance, loss of stability, and a conjecture about turbulent cascade and dissipation rates. Physics of Fluids, 10, 3178-3184.

McWilliams, J. C., C. -H. Moeng, and P. P. Sullivan, 1999: Turbulent fluxes and coherent structures in marine boundary layers: Investigations by Large-Eddy Simulation. Air-Sea Exchange: Physics, Chemistry, Dynamics, and Statistics, G. Geernaert, Ed., Kluwer Academic Publishers, 507-538.

McWilliams, J. C., and P. P. Sullivan, 2001: Surface-wave effects on winds and currents in marine boundary layers. Environmental Fluid Dynamics, J. Lumley, Ed., Sringer-Verlag, accepted for publication.

Meehl, G. A., 1998: Climate modeling. Meteorology of the Southern Hemisphere, D. Karoly and D. Vincent, Eds., American Meteorological Society, 365-410.

Meehl, G. A., 1998: Scale interactions in atmosphere, ocean and coupled models. Climatic Impact of Scale Interactions for the Tropical Ocean-Atmosphere System, J. Slingo, P. Delecluse, and G. Komen, Eds., Euroclivar Publication 13, 44–45.

Meehl, G. A., J. W. Hurrell, and H. van Loon, 1998a: A modulation of the mechanism of the semiannual oscillation in the Southern Hemisphere. Tellus, 50A, 442-450.

Meehl, G. A., J. M. Arblaster, W. G. Strand Jr., 1998b: Global scale decadal climate variability, Geophys. Res. Lett, 25, 3983-3986

Meehl, G. A., and J. M. Arblaster, 1998: The Asian-Australian monsoon and El Niño-Southern Oscillation in the NCAR Climate System Model. J. Climate, 11, 1356-1385.

Meehl, G. A., W. M. Washington, J. M. Arblaster, T. W. Bettge, and W. G. Strand, Jr., 2000a: Anthropogenic forcing and decadal climate variability in sensitivity experiments of 20th and 21st century climate. J. Climate, 13, 3728-3744.

*Meehl, G. A., W. D. Collins, B. Boville, J. T. Kiehl, T. M. L Wigley, and J. M. Arblaster, 2000b: Response of the NCAR Climate System Model to increased CO₂ and the role of physical processes. J. Climate, 13, 1879-1898.

Meehl, G. A., G. J. Boer, C. Covey, M. Latif, and R. J. Stouffer, 2000c: The Coupled Model Intercomparison Project (CMIP). Bull. Amer. Meteor. Soc., 81, 313-318.

Meehl, G. A., T. Karl, D. R. Easterling, S. Changnon, R. Pielke, Jr., D. Changnon, J. Evans, P. Ya Groisman, T. R. Knutson, K. Kunkel, L. O. Mearns, C. Parmesan, R. Pulwarty, T. Root, R. B. Street, R. T. Sylves, P. Whetton, and F. Zwiers, 2000d: An introduction to trends in extreme weather and climate events: Observations, socio-economic impacts, terrestrial ecological impacts, and model projections. Bull. Amer. Meteor. Soc., 81, 413-416.

Meehl, G. A., F. Zwiers, J. Evans, T. Knutson, L. O. Mearns, and P. Whetton, 2000e: Trends in extreme weather and climate events: Issues related to modeling extremes in projections of future climate change. Bull. Amer. Meteor. Soc., 81, 427-436.

Meehl, G. A., J. M. Arblaster, and W. G. Strand, Jr., 2000f: Sea ice effects on climate model sensitivity and low frequency variability. Climate Dyn., 16, 257-271.

Meehl, G. A., P. Gent, J. M. Arblaster, B. Otto-Bliesner, E. Brady, and A. Craig, 2001a: Factors that affect amplitude of El Niño in global coupled climate models. Climate Dyn., accepted for publication.

Meehl, G. A., R. Lukas, G. N. Kiladis, M. Wheeler, A. Matthews, and K. M. Weickmann, 2001b: A conceptual framework for time and space scale interactions in the climate system. Climate Dyn., accepted for publication.

Meiring, W., P. Guttorp, and P. D. Sampson, 1999: Space-time estimation of grid-cell hourly ozone levels for assessment of a deterministic model. Environmental and Ecological Statistics, 5, 197-222.

Miller, A. J., J. C. McWilliams, N. Schneider, J. S. Allen, J. A. Barth, R. C. Beardsley, T. K. Chereskin, C. A. Edwards, R. L. Haney, K. A. Kelly, J. C. Kindle, L. N. Ly, J. R. Moisan, M. A. Noble, P. P. Niiler, L. Y. Oey, F. B. Schwing, R. K. Shearman, and M. S. Swenson, 1999: Observing and modeling the California Current System: Purposes, achievements, and aspirations. EOS, 80, 533-539.

Milliff, R. F., T. J. Hoar, and R. A. Madden, 1998: Fast, eastward-moving disturbances in the surface winds of the equatorial Pacific. Tellus, 50A, 26-41.

Milliff, R. F., W. G. Large, J. Morzel, and G. Danabasoglu, 1999: Ocean general circulation model sensitivity to forcing from scatterometer winds. J. Geophys. Res., 104, 11 337-11 358.

Milliff, R. F., T. J. Hoar, H. van Loon, and M. Raphael, 1999: Quasi-stationary wave variability in NSCAT winds. J. Geophys. Res., 104, 11 425–11 436.

Milliff, R. F., and J. Morzel, 2000: The global distribution of the time-average wind-stress curl from NSCAT. J. Atmos. Sci., 58, 109-131.

Moore, J. K., S. C. Doney, J. A. Kleypas, D. M. Glover, and I. Y. Fung, 2001: An intermediate complexity marine ecosystem model for the global domain. Deep-Sea Research, II, accepted for publication.

Moore, J. K., S. C. Doney, J. A. Kleypas, D. M. Glover, I. Y. Fung, 2001: Iron cycling and nutrient limitation patterns in surface waters of the world ocean. Deep-Sea Research, II, accepted for publication.

Murphy, S. J., H. E. Hurlburt, and J. J. O'Brien, 1999: The connectivity of mesoscale variability in the Caribbean Sea, the Gulf of Mexico, and the Atlantic Ocean, J. Geophys. Res., 104, 1431–1453.

Murphy, S., and T. R. Keen, 2000: The sensitivity of relocatable local area models to temporal interpolation noise at open boundaries. J. Atmos. Oceanic Technol., 6, 862-878.

Newton, C. W., and H. R. Newton, 1999: The Life Cycles of Extratropical Cyclones. The Bergen School Concepts Comes to America. M. Shapiro and S. Gronas, Eds., Amer. Meteor. Soc., 41–59.

Nychka, D., 2000: Challenges in understanding the atmosphere. Journal of the American Statistical Association, 95, 972-975.

Ojima, D., L. Garcia, E. Elgaali, K. Miller, T. G. F. Kittel, and J. Lackett, 1999: Potential climate change impacts on water resources in the Great Plains. Journal of the American Water Resources Associatio, 35, 1443-1454.

Otto-Bliesner, B. L., 1998: Effects of tropical mountain elevations on the climate during the past: Climate model experiments. Tectonic Boundary Conditions for Climate Reconstructions, T. J. Crowley and K. C. Burke, Eds., Oxford Monographs on Geology and Geophysics, Chapter 5, Oxford University Press, 100-115.

Otto-Bliesner, B. L., 1999: El Niño/La Niña and Sahel precipitation during the middle Holocene. Geophs. Res. Lett., 26:1, 87-90.

*Otto-Bliesner, B. L., and E. C. Brady, 2001: Tropical Pacific variability in the NCAR Community Climate System Model (CCSM). J. Climate, accepted for publication.

Otto-Bliesner, B. L., 2001: The role of mountains, polar ice, and vegetation in determining the tropical climate during the Middle Pennsylvanian: Climate model simulations, in Middle Pennsylvanian Sedimentation and Climate, C.B. Cecil (Ed.), SEPM Special Volume, accepted for publication.

Pan, Yude, Jerry M. Melillo, A. David McGuire, David W. Kicklighter, Louis F. Pitelka, Kathy Hibbard, Lars L. Pierce, Steven W. Running, Dennis S. Ojima, William J. Parton, David S. Schimel, and other VEMAP members including H. Fisher, T. Kittel, R. McKeown, and N. Rosenbloom, 1998: Modeled responses of terrestrial ecosystems to elevated atmospheric CO₂: A comparison of simulations by the biogeochemistry models of the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP). Oecologia, 114, 389-404.

Parton, W. J., M. Hartman, D. Ojima, and D. Schimel, 1998: DAYCENT and its land surface submodel: Description and testing. Global and Planetary Change, 19, 35-48.

Pawson, S., K. Kodera, K. Hamilton, T. G. Shepherd, S. R. Beagley, B. A. Boville, J. D. Farrara, T. D. A. Fairlie, A. Kitoh, W. Lahoz, U. Langematz, E. Manzini, D. H. Rind, A. A. Scaife, K. Shibata, P. Simon, R. Swinbank, L. Takacs, R. J. Wilson, J. A. Al-Saadi, M. Amodei, M. Chiba, L. Coy, J. de Grandpré, R. S. Eckman, M. Fiorino, W. L. Grose, H. Koide, J. N. Koshyk, D. Li, J. Lerner, J. D. Mahlman, N. A. McFarlane, C. R. Mechoso, A. Molod, A. O'Neill, R. B. Pierce, W. J. Randel, R. B. Rood, F. Wu, 2000: The GCM-reality intercomparison project for SPARC (GRIPS): Scientific Issues and Initial Results. Bull. Amer. Meteor. Soc., 81, 781-796.

Pfaff, A. S. P., S. Kerr, R. F. Hughes, S. G. Liu, G. A. Sanchez-Azofeifa, D. Schimel, J. Tosi, and V. Watson, 2000: The Kyoto protocol and payments for tropical forest: An interdisciplinary method for estimating carbon-offset supply and increasing the feasibility of a carbon market under the CDM. Ecological Economics, 35, 203-221.

Pielke, R. A., Sr. J. Eastman, T. N. Chase, J. Knaff, and T. G. F. Kittel, 1998: 1973-1996 trends in depth-averaged tropospheric temperature. J. Geophys. Res.-Atmospheres, 103, 16 927-16 933.

Qian, J. -H., F. H. M. Semazzi, and J. S. Scroggs, 1998: A global nonhydrostatic semi-Lagrangian atmospheric model with orography. Mon. Wea. Rev., 126, 747-771.

Prather, M., R. Sausen, A. S. Grossman, J. M. Haywood, D. Rind, B. H. Subbaraya, P. Forster, A. Jain, M. Ponater, U. Schumann, W.-C. Wang, T. M. L. Wigley, and D. J. Wuebbles, 1999: Potential climate change from aviation. Aviation and the Global Atmosphere, J. E. Penner, D. H. Lister, D. J. Griggs, D. J. Dokken and M. McFarland, Eds., Cambridge University Press, 185–215.

Ramanathan, V., P. J. Crutzen, J. Lelieveld, D. Althausen, J. Anderson, M. O. Andreae, W. Cantrell, G. Cass, C. E. Chung, A. D. Clarke, W. D. Collins, J. A. Coakley, F. Dulac, J. Heintzenberg, A. J. Heymsfield, B. Holben, J. Hudson, A. Jayaraman, J. T. Kiehl, T. N. Krishnamurti, D. Lubin, A. P. Mitra, G. MacFarquhar, T. Novakob, J. A. Ogren, I. A. Podgorny, K. Prather, J. M. Prospero, K. Priestley, P. K. Quinn, K. Rajeeb, P. Rasch, S. Rupert, R. Sadourny, S. K. Satheesh, P. Sheridan, G. E. Shaw, and F. P. J. Valero, 2000: The Indian Ocean Experiment: An integrated assessment of the climate forcing and effects of the great Indo-Asian haze. Journal of Geophysical Research, accepted for publication.

Rasch, P. J., and J. E. Kristjansson, 1998: A comparison of the CCM3 model climate using diagnosed and predicted condensate parameterizations. J. Climate, 11, 1587-1614.

Rasch, P. J., M. C. Barth, J. T. Kiehl, S. E. Schwartz, and C. M. Benkovitz, 2000: A description of the global sulfur cycle and its controlling processes in the National Center for Atmospheric Research Community Climate Model, Version 3. J. Geophys. Res., 105, 1367-1385.

Rasch, P.J., J. Feichter, K. Law, N. Mahowald, J. Penner, C. Benkovitz, C. Genthon, C. Giannakopoulos, P. Kasibhatla, D. Koch, H. Levy, T. Maki, M. Prather, D. L. Roberts, G. -J. Roelofs, D. Stevenson, Z. Stockwell, S. Taguchi, M. Kritz, M. Chipperfield, D. Baldocchi, P. McMurry, L. Barrie, Y. Balkanski, R. Chatfield, E. Kjellstrom, M. Lawwrence, H.N. Lee, J. Lelieveld, K. J. Noone, J. Seinfield, G. Stenchikov, S. Schwartz, C. Walcek, and D. Williamson, 2000: A comparison of scavenging and deposition processes in global models: Results from the WCRP Cambridge workshop of 1995. Tellus, 52, 1025-1056.

*Rasch, P. J., W. D. Collins and B. E. Eaton, 2001: Understanding the Indian Ocean Experiment (INDOEX) aerosol distributions with an aerosol assimilation. Journal of Geophysical Research, accepted for publication.

Reynolds, C., and R. M. Errico, 1999: Convergence of singular vectors toward Lyapunov vectors. Mon. Wea Rev., 127, 2309-2323.

Rosenbloom, N. A., S. C. Doney, and D. S. Schimel, 2001: Geomorphic evolution of soil texture and organic matter in eroding landscapes. Global Biogeochem. Cycles, accepted for publication.

Rotman, D. A., J. R. Tannahill, D. E. Kinnison, P. S. Connell, D. Bergmann, D. Proctor, J. M. Rodriguez, S. J. Lin, R. B. Rood, M. J. Prather, P. J. Rasch, D. B. Considine, R. Ramaroson, and S. R. Kawa, 2001: Global Modeling Initiative assessment model: Model description, integration, and testing of the transport shell. Journal of Geophysical Research, 106, 1669-1691.

Royle, J. A., L. M. Berliner, C. K. Wikle, and R. F. Milliff, 1998: A hierarchical spatial model for constructing wind fields from scatterometer data in the Labrador Sea. Case Studies in Bayesian Statistics IV, C. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A.Gelman, I. Verdinelli, and M. West, Eds., Springer-Verlag, 367-382.

Royle, J. A., and L. M. Berliner, 1999: A hierarchical approach to multivariate spatial modeling and prediction. J. Agricultural, Biological, and Environmental Statistics, 4, 29–56.

Santer, B. D., J. J Hnilo, T. M. L Wigley, J. S. Boyle, C. Doutriaux, M. Fiorino, D. E. Parker, and K. E. Taylor, 1999: Uncertainties in observationally based estimates of temperature change in the free atmosphere. J. Geophys. Res., 104, 6305–6333.

Santer, B. D., T. M. L Wigley, D. J. Gaffen, L. Bengtsson, C. Doutriaux, J. S. Boyle, M. Esch, J. J. Hnilo, P. D. Jones, G. A. Meehl, E. Roeckner, K. E. Taylor, and M. F. Wehner, 2000a: Interpreting differential temperature trends at the surface and in the lower troposphere. Science, 287, 1227-1232.

Santer, B. D., T. M. L. Wigley, J. S. Boyle, D. J. Gaffen, J. J. Hnilo, D. Nychka, D. E. Parker, and K. E. Taylor, 2000b: Statistical significance of trends and trend differences in layer-average temperature time series. J. Geophys. Res., 105, 7337-7356.

*Saravanan, R., 1998: Atmospheric low-frequency variability and its relationship to midlatitude SST variability: Studies using the NCAR Climate System Model. J. Climate, 11, 1386-1404.

Saravanan, R., and J. C. McWilliams, 1998: Advective ocean-atmosphere interaction: An analytical stochastic model with implications for decadal variability. J. Climate, 11, 165-188.

Saravanan, R., G. Danabasoglu, S. C. Doney, and J. C. McWilliams, 1999: Decadal variability and predictability in the midlatitude ocean-atmosphere system. J. Climate, 13, 1073-1097.

Saravanan, R., and P. Chang, 2000: Interaction between tropical Atlantic variability and El Niño-Southern Oscillation. J. Climate, 13, 2177-2194.

Saravanan, R., and P. Chang, 2000: Oceanic mixed layer feedback and tropical Atlantic variability. Geophys. Res. Lett., 26, 3629-3632.

Schimel, D. S, 1998: Climate change, the carbon equation. Nature, 393, 208-209.

Schimel, D. S., and N. S. Panikov, 1999: Simulation models of terrestrial trace gas fluxes at soil microsites to global scales. Approaches to Scaling of Trace Gas Fluxes in Ecosystems, L. Bouwman, Ed., Elsevier Science, Amsterdam, 185-202.

Schimel, D., J. Melillo, H. Tian, A. D. McGuire, D. Kicklighter, T. Kittel, N. Rosenbloom, S. Running, P. Thornton, D. Ojima, W. Parton, R. Kelly, M. Sykes, R. Neilson, and B. Rizzo, 2000: Contribution of increasing CO₂ and climate to carbon storage by ecosystems in the United States. Science, 287, 2004-2006.

Schneider, N., A. J. Miller, M. A. Alexander, and C. Deser, 1998: Subduction of decadal North Pacific temperature anomalies: Observations and dynamics. J. Phys. Oceanogr., 29, 1056-1070.

Schneider, T., C. Granier, X. X. Tie, and D. Hauglustaine, G. B. Bonan, and L. M. Stillwell-Soller, 1998: Soil water and the persistence of floods and droughts in the Mississippi River Basin. Water Resour. Res., 34, 2693-2701.

Schneider, N., S. Venzke, A. J. Miller, D. W. Pierce, T. P. Barnett, C. Deser and M. Latif, 1999: Pacific thermocline bridge revisited. Geophys. Res. Lett., 26, 1329–1332.

Schubert, S. D., M. J. Suarez, Y. Chang, and G. Branstator, 2001: The impact of ENSO on extratropical low frequency noise in seasonal forecasts. J. Climate, accepted for publication.

Shukla, J., J. Anderson, D. Baumhefner, C. Brankovic, Y. Chang, E. Kalnay, L. Marx, T. Palmer, D. Paolino, J. Ploshay, S. Schubert, D. Straus, M. Suarez, and J. Tribbia, 2000: Dynamical seasonal prediction. Bull. Amer. Meteor. Soc., 81, 2593-2606.

Shchepetkin, A., and J. C. McWilliams, 1998: Quasi-monotone advection schemes based on explicit locally adaptive dissipation. Mon. Wea. Rev., 126, 1541-1580.

Smith, R. D., M. E. Maltrud, F. O. Bryan, and M. W. Hecht, 1999: Numerical simulation of the North Atlantic Ocean at 1/10°. J. Phys. Oceanogr., 30, 1532-1561.

Smith, S. J., and T. M. L. Wigley, 2000: Global warming potentials: 1. Climatic implications of emissions reductions. Climatic Change, 44, 445-457.

Smith, S. J., and T. M. L. Wigley, 2000: Global warming potentials: 2. Accuracy. Climatic Change, 44, 459-469.

Smith, S. J., H. Pitcher, and T. M. L. Wigley, 2001: Global and regional anthropogenic sulfur dioxide emissions. Global and Planetary Change, accepted for publication.

Smith, S. J., T. M. L. Wigley, N. Nakicenovic, and S. C. B. Raper, 2000: Climate implications of preliminary greenhouse gas emissions scenarios. Technological Forecasting and Social Change, 65, 195-204.

Smith, S. J., T. M. L. Wigley, and J. A., Edmonds, 2000: A new route toward limiting climate change? Science, 290, 1109-1110.

Sneddon, G., 1999: Smoothing in an underdetermined linear model with random explanatory variables. Canadian Journal of Statistics, 27, 63-79.

Stenseth, N. C., and Co-authors, 1999: Common dynamic structure of Canadian Lynx populations within three geo-climatic zones. Science, 285, 1071-1073.

Stocker, T., G. K. C. Clarke, H. Le Treut, R. S. Lindzen, V. P. Meleshko, R. K. Mugara, T. N. Palmer, R. T. Pierrehumbert, P. J. Sellers, K. E. Trenberth, and J. Willebrand, 2001: Physical Climate Processes and Feedbacks. Chapter 7 of Climate Change 2000. The Science of Climate Change. Contribution of WG 1 to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J. T. Houghton, D. Griggs et al. (eds). Cambridge University Press, submitted.

Stohlgren, T. J., T. N. Chase, R. A. Piekle Sr., T. G. F. Kittel, and J. Baron, 1998: Evidence that local land use practices influence regional climate, vegetation, and stream flow patterns in adjacent natural areas. Global Change Biology, 4, 495-504.

Sullivan, P. P., J. C. McWilliams, and C. -H. Moeng, 1999: Simulation of turbulent flow over idealized water waves. J. Fluid Mech., 404, 47-85.

Sun, D. -Z., and K. E. Trenberth, 1998: Coordinated heat removal from the tropical Pacific during the 1986-87 El Niño. Geophys. Res. Lett., 25, 2659-2662.

Sutyrin, G. G, J. C. McWilliams, and R. Saravanan, 1998: Co-rotating stationary states and vertical alignment of geostrophic vortices with thin cores. J. Fluid Mech., 357, 321-349.

Tailleux, R., and J. C. McWilliams, 2000: Acceleration, creation, and depletion of wind-driven, baroclinic Rossby waves over an ocean ridge. J. Phys. Oceanogr., 30, 2186-2213.

Tailleux, R., and J. C. McWilliams, 2001: The effect of bottom-pressure decoupling on the speed of extratropical, baroclinic Rossby waves. J. Phys. Oceanogr., accepted for publication.

Tierney, C., J. Wahr, F. Bryan, and V. Zlotnicki, 2000: Short-period oceanic circulation: Implications for satellite altimetry. Geophys. Res. Lett., 27, 1255-1258.

Tebaldi, C., and M. West, 1998: Bayesian inference on network traffic using link count data (with discussion). Journal of the American Statistical Association, 93, 557-576.

Trenberth, K. E., 1998: Atmospheric moisture residence times and cycling: Implications for rainfall rates with climate. Clim. Change, 39, 667-694.

Trenberth, K. E., and C. J. Guillemot, 1998: Evaluation of the atmospheric moisture and hydrological cycle in the NCEP/NCAR reanalyses. Climate Dyn., 14, 213-231.

Trenberth, K. E., G. W. Branstator, D. Karoly, A. Kumar, N. -C. Lau, and C. Ropelewski, 1998: Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res., 103, 14 291-14 324.

Trenberth, K. E., et al.,1998: The CLIVAR Initial Implementation Plan. WCRP 103, WMO/TD No. 869, ICPO 14, 356 pp.

Trenberth, K. E., and C. J. Guillemot, 1998: Estimating evaporation-minus-precipitation as a residual of the atmospheric water budget. Global Energy and Water Cycles, K. Browning and R. Gurney, Eds., Cambridge University Press, 236–246.

Trenberth, K. E., 1999: Short-term Climate Variations. Recent accomplishments and issues for future progress. Storms. Vol 1, R. Pielke Sr. and R. Pielke Jr., Eds., Routledge Press, 126-141.

Trenberth, K. E., 1999: Global climate project shows early promise. Eos, 80, 274-275.

Trenberth, K. E., 1999: The climate system and climate change. Current topics in Wetland Biogeochemistry, 3, 4-15.

Trenberth, K. E., 1999: The extreme weather events of 1997 and 1998. Consequences, 5, 1, 2‑15.

Trenberth, K. E., 1999: Atmospheric moisture recycling: Role of advection and local evaporation. J. Climate, 12, 1368–1381.

Trenberth, K. E., 1999: Conceptual framework for changes of extremes of the hydrological cycle with climate change. Clim. Change, 42, 327–339.

Trenberth, K. E., and J. M. Caron, 2001: Estimates of meridional atmosphere and ocean heat transports. J. Climate, submitted.

Trenberth, K. E., and T. Owen, 1999: Workshop on indices and indicators for climate extremes. Breakout Group A: Storms. Clim. Change, 42, 9-21.

Trenberth, K. E., and J. W. Hurrell, 1999: Reply to Rajagopalan, Lall and Cane's comment about "The interpretation of short climate records with comments on the North Atlantic and Southern Oscillations.'' Bull. Amer. Met. Soc., 80, 2726-2728.

Trenberth, K. E., and J. W. Hurrell, 1999: Comment on "The interpretation of short climate records with comments on the North Atlantic and Southern Oscillations." Bull. Amer. Met. Soc., 80, 2721-2722.

Trenberth, K. E., 2001: Earth system processes and interactions. Encyclopedia of Global Environmental Change, Vol. 1, John Wiley & Sons Ltd., accepted for publication.

Trenberth, K. E., 2000: Millennium Perspectives. Bull. Amer. Meteor. Soc., 81, 100.

Trenberth, K. E., and J. M. Caron, 2000: The Southern Oscillation revisited: Sea level pressures, surface temperatures and precipitation. J. Climate, 13, 4358-4365.

Trenberth, K. E., D. P. Stepaniak, and J. M. Caron, 2000: The global monsoon as seen through the divergent atmospheric circulation. J. Climate, 13, 3969-3993.

Trenberth, K. E., K. Miller, L. Mearns, and S. Rhodes, 2000: Effects of Changing Climate on Weather and Human Activities. University Science Books, 46 pp.

Trenberth, K. W., and D. P. Stepaniak, 2001: Indices of El Niño Evolution. J. Climate, 14, 1697-1701.

Trenberth, K. E., D. P. Stepaniak, and J. M. Caron, 2001: The atmospheric energy budget and implications for surface fluxes and ocean heat transports. Climate Dyn., 17, 259-276.

Trenberth, K. E., D. P. Stepaniak, J. W. Hurrell, and M. Fiorino, 2001: Quality of reanalyses in the tropics. J. Climate, 14, 1499-1510.

Upchurch, G. R., Jr., B. L. Otto-Bliesner, and C. R. Scotese, 1998: Vegetation-atmosphere interactons and their role in global warming during the latest Cretaceous. Phil. Trans. R. Soc. Lond. B, 353, 1-17.

Upchurch, G. R., Jr., B. L. Otto-Bliesner, and C. R. Scotese, 1999: Terrestrial vegetation and its effects on climate during the latest Cretaceous, Chapter 21 in Evolution of the cretaceous Ocean-Climate System, Special paper 332, E. Barrera and C. Johnson, Eds., The Geological Society of America, 407-426.

van Hees, R. M., J. Lelieveld, and W. D. Collins, 1999: Detecting tropical convection using AVHRR satellite data. J. Geophys. Res., 104, 9213-9228.

van Loon, H., G. A. Meehl, and J. M. Arblaster, 1998: Global scale decadal climate variability. Geophys. Res. Lett., 25, 3983.

van Loon, H., and K. Labitzke, 1998: The global range of the stratospheric decadal wave. Part I: Its association with the sunspot cycle in summer and in the annual mean, and with the troposphere. J. Climate, 11, 1529-1537.

van Loon, H., and K. Labitzke, 1999: The signal of the 11-year solar cycle in the global stratosphere. J. Atmos. Terr. Phys., 61, 53-61.

van Loon, H., and D. J. Shea, 1999: A probable signal of the 11-year solar cycle in the troposphere of the Northern Hemisphere. Geophys. Res. Lett. 26, 2893-2896.

van Loon, H., and D. Shea, 2000: The global 11-year solar signal in July–August. Geophy. Res. Lett., 27, 2965-2968.

van Loon., H., and K. Labitzke, 2000: The influence of the 11-year solar cycle on the stratosphere below 30 km: a review. Space Sci. Rev., 94, 259–278.

von Hardenberg, J., J. C. McWilliams, A. Provenzale, A. Shchepetkin, and J. B. Weiss, 2001: Vortex merging in quasigeostrophic flows. J. Fluid Mech., accepted for publication.

Wahr, J., M. Molenaar, and F. Bryan, 1998: Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE. J. Geophys. Res., 103 (B12), 30 205-30 229.

Wainer, I., F. O. Bryan, and J. Soares, 1999: Dynamics of the equatorial undercurrent in a high-resolution ocean model. J. Geophys. Res., 104, 23 327-23 335.

Wainer, I., P. R. Gent and G. Goni, 2000: The annual cycle of the Brazil-Malvinas confluence region in the NCAR Climate System Model. Journal of Geophysical Research., 105, 26,176–26,178.

Walko, R. L., L. E. Band, J. Baron, T. G. F. Kittel, R. Lammers, T. J. Lee, R. A. Pielke, Sr., C. Taylor, C. Tague, C. J. Tremback, and P. L. Vidale, 2000: Coupled atmosphere-biophysics-hydrology models for environmental modeling. Journal of Applied Meteorology, 39, 931-944.

Wang, D., J .C. McWilliams, and W. G. Large, 1998: Large eddy simulation of the diurnal cycle of deep equatorial turbulence. J. Phys. Oceanogr., 28, 129-148.

Wanninkhof, R., S. C. Doney, T. -H. Peng, J. Bullister, K. Lee, and R. A. Feely, 1998: Comparison of methods to determine the anthropogenic CO₂ invasion into the Atlantic Coast. Tellus, 51B, 511-530.

Wanninkhof, R., S. C. Doney, T. Takahashi, and W. McGillis, 2001: The effect of using averaged winds on global air-sea CO₂ fluxes. Gas Transfer at Air-Water Interfaces, American Geophysical Union Monograph, American Geophysical Union, accepted for publication.

Washington, W. M., J. W. Weatherly, G. A. Meehl, A. J. Semtner, Jr., T. W. Bettge, A. P. Craig, W. G. Strand, Jr., J. M. Arblaster, V. B. Wayland, R. James, and Y. Zhang, 2000: Parallel Climate Model (PCM) control and transient simulations. Climate Dyn., 16, 755-774.

Welch, W. T., P. Smolarkiewicz, R. Rotunno, and B. Boville, 2001: The large scale effects of flow over periodic mesoscale topography. Journal of Atmospheric Science., accepted for publication.

Weiss, J. B., A. Provenzale, and J. C. McWilliams, 1998: Lagrangian dynamics in high-dimensional point-vortex systems. Phys. Fluids, 10, 1929-1941.

Weatherly, J. W., B. P. Briegleb, W. G. Large, and J. A. Maslanik, 1998: Sea ice and polar climate in the NCAR CSM. J. Climate, 11, 1472-1486.

Wigley, T. M. L., 1998: The Kyoto Protocol: CO₂, CH₄ and climate implications. Geophys. Res. Lett., 25, 2285-2288.

Wigley, T. M. L., R. L. Smith, and B. D. Santer, 1998: Anthropogenic influence on the autocorrelation structure of hemispheric-mean temperatures. Science, 282,1676-1679.

Wigley, T. M. L., P. J. Jaumann, B. D. Santer, and K. E. Taylor, 1999: Relative detectability of greenhouse-gas and aerosol climate change signals. Climate Dyn., 14, 781-790.

Wigley, T.M.L., R. L. Smith and B. D. Santer, 1999: The autocorrelation function and human influences on climate (response to comment by Tsonis and Elsner). Science, 285 (Technical Comment), 495a.

Wigley, T. M. L., B. D. Santer, and K. E. Taylor, 2000: Correlation approaches to detection. Geophys. Res. Lett., 27, 2973-2976.

Wigley, T. M. L., 2000: Stabilization of CO₂ concentration levels. The Carbon Cycle, T. M. L. Wigley and D. S. Schimel, Eds., Cambridge University Press, 258-276.

Wigley, T. M. L., and D. S. Schimel, 2000: The Carbon Cycle. Cambridge University Press, 292 pp.

Wigley, T. M. L., 2000: ENSO, volcanoes and record breaking temperatures. Geophysical Research Letters, 27, 4101-4104.

Wigley, T. M. L., 1999: The Science of Climate of Climate Change: Global and U.S. Perspectives. Pew Center on Global Climate Change, 48 pp.

Wikle, C. K., R. F. Milliff, and W. G. Large, 1999: Surface wind variability on spatial scales from 1 to 1000 km observed during TOGA COARE. J. Atmos. Sci., 56, 2222-2231.

Wikle, C. K., L. M. Berliner, and N. Cressie, 1999: Hierarchical Bayesian space-time models. Environmental and Ecological Statistics, 5, 117-154.

Wikle, C. K., R. F. Milliff, D. Nychka, and L. M. Berliner, 2001: Spatio-temporal hierarchical Bayesian modeling: Tropical ocean surface winds. Journal of the American Statistical Assoc., Applications, accepted for publication.

Wilby, R. L., 1998: Hydrological impacts of the National Forest. East Midlands Geographer, 21, 71-77.

Wilby, R. L., H. Hassan, and K. Hanaki, 1998: Statistical downscaling of hydrometeorological variables using general circulation model output. J. Hydrol., 205, 1-19.

Wilby, R. L., L. E. Cranston, and E. J. Darby, 1998: Factors governing macrophyte status in Hampshire chalk streams: Implications for catchment management. The Journal of the Chartered Institution of Water and Environmental Management, 12, 179-187.

Wilby, R. L., 1998: Modelling extreme rainfall using weather pattern and frontal frequencies. J. Hydrol., 212–213, 380–392

Wilby, R. L., 1998: Statistical downscaling of daily precipitation using daily airflow and seasonal teleconnection indices. Climate Research, 10, 163–178.

Wilby, R. L., T. M. L. Wigley, D. Conway, P. D. Jones, B. C. Hewitson, J. Main, and D. S. Wilks, 1998: Statistical downscaling of general circulation model output: A comparison of methods. Water Resour. Res., 34, 2995-3008.

Wilby, R. L., 1999: The future of eco-hydrology. Eco-Hydrology: Plants and water in terrestrial and aquatic environments, A. Baird and R. L. Wilby, Eds., Routledge Physical Environment Series, 346–374.

Wilby, R. L., L. E. Hay, and G. H. Leavesley, 1999: A comparison of downscaled and raw GCM output: Implications for climate change scenarios in the San Juan River basin, Colorado. Journal of Hydrology, 225, 67-91.

Wilby, R. L., and D. S. Schimel, 1999: Scales of interaction in eco-hydrological relations. Eco-Hydrology: Plants and water in terrestrial and aquatic environments, A. Baird and R. L. Wilby, Eds., Routledge Physical Environment Series, 39–77.

Wilby, R. L. 2000: Classics in physical geography revisited: Lamb, H. H. 1950: Types and spells of weather around the year in the British Isles. Progress in Physical Geography, 24, 379-383.

Wilby, R. L., 2001: Seasonal forecasting of UK river flows using preceding North Atlantic pressure patterns. Journal of the Chartered Institution of Water and Environmental Management, in press.

Wilby, R. L., 2001: Data acquisition and downscaling for studies of future climate. Climate Change and Soil Erosion, J. Boardman and D. Favis–Mortlock, Eds., Imperial College Press, accepted for publication.

Wilby, R. L., 2001: The hydrology of drought. Rivers Handbook Volume III: Drought in the Humid Temperate Zone, G. E. Petts and G. McGregor, Eds., Blackwell Science Ltd., in press.

Wilby, R. L., D. Conway, and P. D. Jones, 2001: Prospects for downscaling seasonal precipitation variability using conditioned weather generator parameters. Hydrological Processes, in press.

Wilby, R.L., and M. D. Dettinger, 2000: Streamflow changes in the Sierra Nevada, CA simulated using a statistically downscaled General Circulation Model scenario of climate change. Linking Climate Change to Land Surface Change, S. J. McLaren, and D. R. Kniveton, Eds., Kluwer Academic Publishers, 99-121.

Wilby, R. L., L. E. Hay, W. J. Gutowski, R. W. Arritt, E. S. Tackle, Z. Pan, G. H. Leavesley, and M. P. Clark, 2000: Hydrological responses to dynamically and statistically downscaled climate model output. Geophys. Res. Lett., 27, 1199-1202.

Wilby, R. L., and O. J. Tomlinson, 2000: The "Sunday Effect" and weekly cycles of winter weather in the UK. Weather, 55, 214-222.

Wilby, R. L., and T. M. L. Wigley, 2000: Precipitation predictors for downscaling: Observed and general circulation model relationships. International Journal of Climatology, 20, 641-661.

Wilby, R. L., and T. M. L. Wigley, 2001: Downscaling General Circulation Model output: a reappraisal of methods and limitations. Climate Prediction and Agriculture. Proceedings of the START/WMO International Workshop, Geneva, Switzerland, 27-29 September 1999, M. V. K. Sivakumar, Ed., International START Secretariat, in press.

Wild, R., G. O'Hare, and R. L. Wilby, 2000: An analysis of heavy snowfalls/blizzards/snowstorms greater than 13 cm across Great Britain between 1861 and 1996. J. Meteorl., 25, 41-49.

Wilks, D. S., and R. L. Wilby, 1999: The weather generation game: a review ofstochastic weather models. Progress in Physical Geography, 23, 329-357.

Williamson, D. L., 1999: Numerical approximations for global atmospheric models. Global Energy and Water Cycles, K. Browning and R.J. Gurney, Eds., Cambridge University Press, 33-43.

Williamson, D. L., J. G. Olson, and B. A. Boville, 1998: A comparison of semi-Lagrangian and Eulerian tropical climate simulations. Mon. Wea. Rev., 126, 1001-1012.

Williamson, D. L., and J. M. Rosinski, 2000: Accuracy of reduced grid calculations. Quart. J. Roy. Meteorl. Soc., 126, 1619-1640.

Wu, X., W. D. Hall, W. W. Grabowski, M. W. Moncrieff, W. D. Collins, and J. T. Kiehl, 1999: Long-term behavior of cloud systems in TOGA COARE and their interactions with radiative and surface processes, part II: Effects of microphysics on cloud-radiation interaction. Journal of Atmospheric Science, 56, 3177--3195.

Yano, J. –I., M. W. Moncrieff, and J. C. McWilliams, 1998: Linear stability and single-column analyses of several cumulus parameterization categories in a shallow-water model. Quart. J. Roy. Meteor. Soc., 124, 983-1005.

Yates, D. N., T. G. F. Kittel, and R. F. Cannon, 2000: Comparing the correlative Holdridge model to mechanistic biogeographical models for assessing vegetation distribution response to climatic change. Climatic Change, 44, 59-87.

Zhang, M. H., W. Y. Lin, and J. T. Kiehl, 1998: Bias of atmospheric shortwave absorption in the NCAR Community Climate Models 2 and 3: Comparison with monthly ERBE/GEBA measurements. Geophys. Res. Lett., 103, 8919-8925.

Zhang, G. J., J. T. Kiehl, and P. J. Rasch, 1998: Response of climate simulation to a new convective paramaterization in the National Center for Atmospheric Research Community Climate Model (CCM3). J. Climate, 11, 2097-2115.

B. Inventions, Patent Applications, and Patents

This section is not applicable to CGD. We do not have any inventions, patent applications, or patents pending.

IX. MANAGEMENT INFORMATION

A. Management Plan

Managing the activities within CGD is designed around planning, operating, evaluating and determining needed recourses. Our management plan provides the environment and sets the direction so we can accomplish our research objectives and strive to reach our scientific goals. We have tools to help us manage, including advisory groups, documented plans, staff meetings, section head meetings, workshops, program reviews and performance evaluations.

The division is made up of a diverse staff, divided into six research sections, the Geophysical Statistics Program, and a computer information services support group. The research sections are: Climate Analysis Section, Climate Modeling Section, Ecosystem Dynamics and the Atmosphere Section, Global Dynamics Section, Climate Change Research Section, and Oceanography Section. The sections have been determined along related areas of climate research, and there is strong interaction among the various sections. Each section is lead by a section head.

The basis for our activities are the goals and objectives described in our strategic plan. These were set in the context of the overall goals and objectives described in "UCAR 2001" and the 1997 UCAR "Proposal for a new Cooperative Agreement with NSF." Our objectives define the scientific direction in which we are headed, a kind of road map. They were determined based on the knowledge of the division director and scientists as to the research activities to be accomplished to achieve our objectives. Our scientists interact with scientists from universities, national laboratories, and other research organizations. Our director remains abreast similarly, interacting with program managers from NSF and other research institutions.

We held an all CGD staff meeting for each person to participate in describing our goals and objectives. Doing so provided a common understanding of what the division is trying to accomplish. It also allowed for a bottom up process encouraging others' ideas and an opportunity for peer review. Once established, we translated the activities into tasks and actions, and defined jobs and assigned responsibilities to accomplish the tasks. Built into this process is a sense of teamwork.

We match up resources and budget to enable the detailed tasks to be accomplished. This is described annually in our NSF Program Plan. Scientists and support staff communicate as needed to maintain focus on the tasks at hand, identify problems and resolve them. The division office supports the staff in terms of resources, training, proper ergonomics, and flex place and flextime as prescribed by UCAR policies. We review accomplishments through scientific publications, reports, reviews, workshops and individual performance appraisals. We then determine if the accomplishments are consistent with the progress needed to meet our objectives. If there is a noticeable difference, we develop corrective actions to get us back on track or deliberate if we need to adjust our plans.

Each month the CGD director participates in the NCAR Directors Committee meeting and in the UCAR Management Committee (UMC) meeting. Often discussions are about research program and policy issues. In CGD, we hold Section Head meetings monthly. We discuss the Director's Committee meeting and the UMC, program problems, budget concerns, human resources activities and determination of which scientific visitors to invite to the division. The agenda for these meetings is available to the section heads before the meeting to facilitate communication links throughout the division. After each meeting, summary notes are included in a CGD newsletter and distributed division-wide.

Within CGD the Senior Scientist Advisory Committee (SSAC) helps guide the division. This committee meets regularly in December and as needed throughout the remainder of the year. The December meeting is a discussion of possible candidates to proceed, or not, through the Appointments Review Group (ARG) process, which determines advancement. SSAC holds other meetings to discuss the scientific activities and priorities of the division.

Integrated into the division management scheme is the management structure for the CCSM. The objective of managing the CCSM is to build a CCSM community of users who are interested in participating in this project. In June 2000, we published the "Community Climate System Model Plan 2000-2005." This plan describes the areas of science research, the areas of model development and improvements and the framework for managing the program. To promote meaningful participation of those interested, the following management structure is in place.

The CCSM Scientific Steering Committee (SSC) provides scientific leadership for the CCSM project, including oversight of activities of working groups, coordination of model experiments, decision making on model definition and development, encouragement of external participation in the project and promotion of CCSM with NSF and other agencies, as appropriate.

The CCSM Advisory Board (CAB) serves as an advisory committee advising the CCSM Scientific Steering Committee, NSF Program Director, NCAR Director, and UCAR President. The CAB meets regularly (approximately twice per year) and listens to the accomplishments in CCSM development and use. They make recommendations to the leadership of CCSM and to the managers mentioned above.

The primary goal of the CCSM SSC and the CCSM Working Groups is to promote collaboration and efficient development of the CCSM. The CCSM SSC and CCSM Working Groups encourage smaller activities to work in cooperation with the larger CCSM projects. The detailed work on various aspects of CCSM is done in working groups. These working groups consist of scientists who come together to work on topics on which they share common interest. These groups are inclusive. The working groups encourage scientists to participate in cooperative research to minimize unnecessary duplication and competition, so that improvements to CCSM can be made and so that high-quality uses of the CCSM can be achieved.

The CGD CCSM scientists group and CCSM software engineers group meet weekly to discuss the progress of the CCSM. In the meetings, they discuss achievements made, near term plans, and any problems encountered. These meetings allow all to understand what tasks are finished and what has yet to be done. The union of the various CCSM component models depends on interacting with the other models through the coupler. It is important, therefore, that all are aware of the configuration design development and progress in general.